{ "schema_version": "image_classification_explanation_audit_v1", "created_utc": "2026-10-15T09:26:10.840384+00:00", "protocol_sha256": "736096da318220195b03c1c62d21a07e89fef5c86b06e5079d40bc32ffe79a2c", "evaluation_results_sha256": "4f0caab9e641715dbea89aa535113c051284ad8cb2ebd1fffc265904d7c1d46f", "control_audit_sha256": "d1fd5a0bb450c5fe0a4274a96109b423e3c425b277520b9c1777de2ac1be05ba", "reviewed_public_response_count": 37, "review_policy": "Every completed first-attempt main and permutation public answer was read in full. Only public content/explanation were displayed; private reasoning was not inspected. Missing answers are not scored.", "scoring_note": "supported mechanism_alignment means the material mechanism is consistent with relevant code and measured controls at its stated certainty, not uniquely proven. Wrong ranking does not automatically make a hedged mechanism incorrect. comparison_coverage and answer_consistency concern coverage/coherence separately from truth.", "records": [ { "question_id": "q_8a36fc443f07ff9476da1cb066a63d67", "model": "gpt-6-luna", "ranking_correct": true, "summary_zh": "正确识别空间网格的直接位置读出、坐标交互的学习成本和有限训练预算；预测与两条确认差异一致，机制仍是非唯一解释。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "supported", "causal_calibration": "supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "C adds coordinate channels, which can let local features encode absolute location before global averaging", "judgment": "supported", "assessment": "坐标确实在 stem 前进入；mean 加坐标的完整 train/test CE 均远低于无坐标 mean。其中心矩计算方式尚未直接测量。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "B instead uses a 3×3 spatial pooling grid, retaining coarse location information for the classifier", "judgment": "supported", "assessment": "空间读出机制与代码一致，且在300步下比坐标 mean 的 train/test CE 更低；回答没有把这种有限预算优势写成表达能力定理。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "ce2488504401f8708d4ce7e59ae07f4a24450b957d9f86c98d3624c539ba8e14", "probe": null, "instance_id": "pooling_coordinate_s841902", "actual_comparison_evidence": { "mean": { "node_id": "candidate_c93709ee26aacbc9f437", "mean_train_ce": 1.3854690231382847, "mean_test_ce": 1.385668184608221 }, "coordinate_mean": { "node_id": "candidate_d91d654be99bc328c040", "mean_train_ce": 0.331308702530805, "mean_test_ce": 0.34536808996926993 }, "spatial": { "node_id": "candidate_f9bdfa11ef52bc5e3528", "mean_train_ce": 0.025847295970606865, "mean_test_ce": 0.037714587822847534 }, "coordinate_spatial": { "node_id": "candidate_a644642ee0d58a7cbf09", "mean_train_ce": 0.10882683973613894, "mean_test_ce": 0.13160173430514988 } }, "public_fields_reviewed": [ "content", "explanation" ], "comparison_coverage_note": "已核对两条相邻关系及实际字母映射；此字段评价覆盖范围，不等同于关系预测正确。", "answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_a1af9439f07fdde610fbdc50eea762d9", "model": "gpt-6-luna", "ranking_correct": true, "summary_zh": "重排后的字母与代码对应正确；明确区分坐标表示潜力和300步内学会该表示的难度。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "supported", "causal_calibration": "supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "Coordinates can make features position-sensitive and may help recover location information", "judgment": "supported", "assessment": "对应坐标输入的实际干预，配对测量支持其相对无坐标 mean 的总效果；尚不证明实际计算中心矩。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "C exposes coarse spatial layout directly", "judgment": "supported", "assessment": "正确识别3×3网格向线性头提供位置索引；空间版的完整 train/test CE 同时更低，优化解释一致但非唯一。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "5bedec3f1f5867458cb0102af3c13d40b1446ca0184c4a3402e049207acd841c", "probe": { "type": "letter_permutation", "source_question_id": "q_8a36fc443f07ff9476da1cb066a63d67" }, "instance_id": "pooling_coordinate_s841902", "actual_comparison_evidence": { "mean": { "node_id": "candidate_c93709ee26aacbc9f437", "mean_train_ce": 1.3854690231382847, "mean_test_ce": 1.385668184608221 }, "coordinate_mean": { "node_id": "candidate_d91d654be99bc328c040", "mean_train_ce": 0.331308702530805, "mean_test_ce": 0.34536808996926993 }, "spatial": { "node_id": "candidate_f9bdfa11ef52bc5e3528", "mean_train_ce": 0.025847295970606865, "mean_test_ce": 0.037714587822847534 }, "coordinate_spatial": { "node_id": "candidate_a644642ee0d58a7cbf09", "mean_train_ce": 0.10882683973613894, "mean_test_ce": 0.13160173430514988 } }, "public_fields_reviewed": [ "content", "explanation" ], "comparison_coverage_note": "已核对两条相邻关系及实际字母映射；此字段评价覆盖范围，不等同于关系预测正确。", "answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_fcf232651387ce984a8140da96c318d3", "model": "gpt-6-luna", "ranking_correct": false, "summary_zh": "识别频率、采样和感受野，但把细网格保真优先级用于排序，未抓住stride4在固定预算中的实际学习优势。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "partly_supported", "causal_calibration": "partly_supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "A downsamples by 2 and uses 5×5 block convolutions", "judgment": "supported", "assessment": "模型字段识别正确；主比较同时改变stem采样与block kernel，需结合完整2×3对照。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "B downsamples by 4 before its blocks, risking loss or aliasing of the finer grating patterns", "judgment": "plausible_unmeasured", "assessment": "风险表述有保留，但本次stride4的训练/测试CE都接近零，实际方向不支持把混叠损失作为主导因素；多通道学习式patch投影也不等于标量抽点。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "04d2c6622bfb7af8818fb69cd5db4b8e56f5ec1f72cddff677185258f87bf436", "probe": null, "instance_id": "kernel_stride_texture_s841901", "actual_comparison_evidence": { "k3_s1": { "node_id": "candidate_ab616a897d11be58391b", "mean_train_ce": 1.3871534438803792, "mean_test_ce": 1.387192951515317 }, "k5_s2": { "node_id": "candidate_149005313738d78a4ed7", "mean_train_ce": 1.235317818241409, "mean_test_ce": 1.2353980402476452 }, "k3_s4": { "node_id": "candidate_aafda8e15a0bbf01406c", "mean_train_ce": 5.727325014248663e-06, "mean_test_ce": 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"supported", "mechanism_alignment": "partly_supported", "causal_calibration": "partly_supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "C’s 0.0001 rate risks underfitting", "judgment": "supported", "assessment": "完整训练CE与测试CE都约1.385，支持固定预算内欠学习，而非仅测试泛化差。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "B’s 0.01 rate is unusually aggressive for this setup and may cause overshooting or unstable final predictions", "judgment": "plausible_unmeasured", "assessment": "0.01实际同时降低完整训练与测试CE。过冲/校准解释未由逐步更新或概率校准实验确认；措辞may不应仅因错序判为机制定理错误。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "3118f6dacdfebddfca4d5582ef8f5fac391a50ba2bc45c9f4e1b76ac24cfeacf", "probe": null, "instance_id": "learning_rate_s841901", "actual_comparison_evidence": { "lr1e4": { "node_id": "candidate_31abb7f5ae858e9f35e8", "mean_train_ce": 1.3848290643654764, "mean_test_ce": 1.3849183171987534 }, "lr1e3": { "node_id": "candidate_6ec59d4186f9b42d6754", "mean_train_ce": 0.5936531231127447, "mean_test_ce": 0.6058920508075971 }, "lr1e2": { "node_id": "candidate_b07779969f06e2a919a4", "mean_train_ce": 0.2570996006147652, "mean_test_ce": 0.2773895292477846 } }, "public_fields_reviewed": [ "content", "explanation" ], "comparison_coverage_note": "已核对两条相邻关系及实际字母映射；此字段评价覆盖范围，不等同于关系预测正确。", "answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_ba675b4af4aaa388d5e0ecb29edac798", "model": "gpt-6-luna", "ranking_correct": false, "summary_zh": "用常见学习率与高步长风险排序；抓住低学习率学习不足，但未预测较大步长在此预算的有效学习。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "partly_supported", "causal_calibration": "partly_supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "B’s 0.0001 rate is likely too conservative to fit as well within the fixed update budget", "judgment": "supported", "assessment": "该候选完整训练CE约1.385，与测试CE接近；这一欠学习判断有实际支持。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "C’s 0.01 rate may make faster early progress, but its large, constant AdamW updates risk overshooting", "judgment": "plausible_unmeasured", "assessment": "风险并非本次主导结果：0.01完整训练/测试CE均低于0.001和0.0001。未测独立校准或局部曲率，不能把错序唯一归因为过冲。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "1ecdaae4e67c223e7f8f408d4e319a51384c7d9e93f0c34dfbd8f5fb36b1d304", "probe": null, "instance_id": "learning_rate_s841902", "actual_comparison_evidence": { "lr1e4": { "node_id": "candidate_68c3418242c7dd2f2c5e", "mean_train_ce": 1.3849177029915154, "mean_test_ce": 1.3846740862354636 }, "lr1e3": { "node_id": "candidate_3e9dff76e192bdb82479", "mean_train_ce": 0.43976016309534316, "mean_test_ce": 0.4430525932548335 }, "lr1e2": { "node_id": "candidate_878848a639e130ad11ad", "mean_train_ce": 0.11298999113532382, "mean_test_ce": 0.11492065699945897 } }, "public_fields_reviewed": [ "content", "explanation" ], "comparison_coverage_note": "已核对两条相邻关系及实际字母映射；此字段评价覆盖范围，不等同于关系预测正确。", "answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_ec5ca80d9651d097f461319ad3cd14b3", "model": "gpt-6.1-sol", "ranking_correct": true, "summary_zh": "代码与5×5感受野计算正确；解释覆盖两对，承认边界信息，并把网格优点限于短预算的易学读出。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "supported", "causal_calibration": "supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "Boundary effects provide some position information, but are a weaker route to the target", "judgment": "supported", "assessment": "没有把mean CNN误称为严格无位置能力；固定300步的mean train/test均接近chance，与较弱实际学习一致。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "I expect that additional learning burden and spatial dilution to outweigh its potential precision advantage at this budget", "judgment": "supported", "assessment": "空间与坐标mean的train/test差异支持这一有限预算解释，但spatial dilution与交互学习成本未被独立分离。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "c20bed671656c15a704f3aff052fab9739ce0b90e0b5dd35dbc0d49ae6086fc7", "probe": null, "instance_id": "pooling_coordinate_s841901", "actual_comparison_evidence": { "mean": { "node_id": 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"causal_calibration": "supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "Overlap and local interaction patterns can still provide some signal, so C is not necessarily limited to chance", "judgment": "supported", "assessment": "有限padding、软边界和局部交互意味着不能仅从全局平均推导严格chance下限。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "That is a less direct optimization route under this short training budget", "judgment": "supported", "assessment": "坐标mean完整训练CE仍高于空间版，符合300步下读出易学程度的解释；不是唯一机制证明。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "a89b7424e0a2f643f2c69865b17e752c40b4afb41979c74497f8ccb8e5bf85d3", "probe": { "type": "letter_permutation", "source_question_id": "q_ec5ca80d9651d097f461319ad3cd14b3" }, "instance_id": "pooling_coordinate_s841901", "actual_comparison_evidence": { "mean": { "node_id": "candidate_3cbaed19cf1f1bd78892", "mean_train_ce": 1.387246625032276, "mean_test_ce": 1.3874168954789639 }, "coordinate_mean": { "node_id": "candidate_fe248f3711cecdf66c13", "mean_train_ce": 0.32638712151674554, "mean_test_ce": 0.33372093125944957 }, "spatial": { 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"assessment": "5×5是正确的局部感受野，但对象可能局部重叠，且边界提供信息；不能把所有样本的关系信息判为不可观察。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "the continuous positional information should win on average", "judgment": "plausible_unmeasured", "assessment": "表示更精细不推出300步后的平均CE更低。回答承认坐标交互更难学，而确认结果支持其自己列出的网格易优化替代解释。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", 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"data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "C’s more direct positional readout should have the optimization advantage at this training budget", "judgment": "supported", "assessment": "完整train/test差异与此预算解释一致；只支持当前设置下总效果和相容机制，不是架构普遍优势。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "2f6e97495d3c7b5d3e6bd23f2c8119d655e91d731ddcf67fec45df9b359e0f80", "probe": { "type": 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"answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_9d3f74e3a6db4ef85ae57f643c6a4f29", "model": "claude-opus-5-5", "ranking_correct": false, "summary_zh": "重排后保持相同结构排序，正确识别支持范围；对stride2更平滑可靠、差距小和容量泛化的判断缺乏观测支撑。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "partly_supported", "causal_calibration": "partly_supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "The effective receptive field is about 2 + 2·4·2 ≈ 18 px", "judgment": "supported", "assessment": "该式是理论支持范围，不是测量出的effective receptive field；数值对应实际卷积链。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", 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"当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "AdamW at 1e‑3 is the well‑tuned regime for a LayerNorm residual CNN this size", "judgment": "unsupported_calibration", "assessment": "没有此设置已调好证据；确认中0.01完整train/test更低。过拟合有限的猜测与当前较小train/test差一致，但不推出默认LR最优。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "ceb5ca2b09b4b2d57cc28eb3667ecbfbd1bd620ac8aa54a4ec7b90aabf40a144", "probe": { "type": "letter_permutation", "source_question_id": "q_a5f2d1e9542f2df31803626953d1af76" }, "instance_id": "learning_rate_s841901", 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}, "annotations": [ { "verbatim_public_quote": "At 1e-4, each parameter can move at most about 0.12 in total over 1200 steps", "judgment": "incorrect", "assessment": "AdamW每步包含偏差校正的一二阶矩比及衰减；该比不恒≤1，lr×步数不是单参数路径或净位移的一般上界。 独立单参数反例在同lr/步数/AdamW超参且梯度均<1时位移0.311685，超过0.12；该反例仅否定普遍上界，不代表这些候选的实际位移。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/explanation_supporting_checks.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "That makes the final weights noisy, with likely loss spikes, miscalibrated or overconfident logits", "judgment": 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"data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "Adam moves each weight by at most about 0.12 in total over 1200 steps", "judgment": "incorrect", "assessment": "AdamW的自适应矩比与decoupled decay使lr×steps不构成此硬上界；不能用它证明学习特征不可能。 独立单参数反例在同lr/步数/AdamW超参且梯度均<1时位移0.311685，超过0.12；该反例仅否定普遍上界，不代表这些候选的实际位移。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", 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"judgment": "incorrect", "assessment": "head输入24变216是9倍权重；含bias100变868约8.68倍。总参数15436变16204约1.05倍，都不是4倍。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "A has no positional information at all", "judgment": "overstated", "assessment": "没有显式坐标与网格不等于无信息：padding和局部交互仍可贡献；实际chance附近是有限训练结果而非信息论证明。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "e0c92780b3bc3b8d45e2bcf1e68605f75c95f0a9aa1d97ad23df65c7a4b142ac", "probe": null, "instance_id": "pooling_coordinate_s841902", "actual_comparison_evidence": { "mean": { "node_id": "candidate_c93709ee26aacbc9f437", "mean_train_ce": 1.3854690231382847, "mean_test_ce": 1.385668184608221 }, "coordinate_mean": { "node_id": "candidate_d91d654be99bc328c040", "mean_train_ce": 0.331308702530805, "mean_test_ce": 0.34536808996926993 }, "spatial": { "node_id": "candidate_f9bdfa11ef52bc5e3528", "mean_train_ce": 0.025847295970606865, "mean_test_ce": 0.037714587822847534 }, "coordinate_spatial": { "node_id": "candidate_a644642ee0d58a7cbf09", "mean_train_ce": 0.10882683973613894, "mean_test_ce": 0.13160173430514988 } }, "public_fields_reviewed": [ "content", "explanation" ], "comparison_coverage_note": "已核对两条相邻关系及实际字母映射；此字段评价覆盖范围，不等同于关系预测正确。", "answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_a1af9439f07fdde610fbdc50eea762d9", "model": "claude-haiku-5-5", "ranking_correct": true, "summary_zh": "正确解释网格直接读出与300步优化，并识别新增stem输入；关于裁剪不重要及差距很小的猜测不受实测支持。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "partly_supported", "causal_calibration": "partly_supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "Gradient clipping at 1.0 is unlikely to be the binding constraint for any choice", "judgment": "plausible_unmeasured", "assessment": "对应spatial与coordinate-mean训练中约76%/62%步骤实际裁剪；说明裁剪活跃，但没有无裁剪控制，仍不能断言其是性能瓶颈。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "the ranking is governed by how easily each architecture reaches a low-loss solution", "judgment": "supported", "assessment": "完整train/test CE同向更低支持有限训练优化解释；不能仅以结构名或参数数确定实际神经表示。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": 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"正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_ededc5c5112d4fee539b6d60dbb9549c", "model": "claude-haiku-5-5", "ranking_correct": true, "summary_zh": "字母映射、预算与机制解释正确；把坐标路径的潜力与短预算内的可学性区分开，未将正确排序当作因果证明。", "scores": { "code_fidelity": "supported", "mechanism_alignment": "supported", "causal_calibration": "supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "the coordinate-plus-mean model could match or beat the spatial-grid model if the coordinate channels are used efficiently", "judgment": "supported", "assessment": "合理保留优化条件；本批spatial train/test优于coordinate-mean，且坐标spatial控制未改善，排除“加信息必然改善”捷径。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "the flattened feature (24×9 = 216 values) keeps coarse position information", "judgment": "supported", "assessment": "正确的维度与读出位置索引；关于24维压缩的叙述不能单独证明信息不足，但正文未提出不可表示保证。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "fdd925ece730444a4225de8fed7901ddc1864ea91ae54e9f8a54fd0c6213714c", "probe": null, "instance_id": "pooling_coordinate_s841903", 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"supported", "mechanism_alignment": "supported", "causal_calibration": "supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "it is indirect and harder to learn in 300 steps", "judgment": "supported", "assessment": "符合spatial与坐标mean完整train/test差异；只是与证据相容，不证明唯一优化机制。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "Padding gives only weak boundary cues", "judgment": "supported", "assessment": "承认finite-image边界，避免严格平移不变推断；未提局部重叠是遗漏，但不改变其有限预算预测的证据边界。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "25152a1b3f68b7ffa43d8df180a08c8e1a34ac77d68ef8964b35ca9cc68719a7", "probe": { "type": "letter_permutation", "source_question_id": "q_ededc5c5112d4fee539b6d60dbb9549c" }, "instance_id": "pooling_coordinate_s841903", "actual_comparison_evidence": { "mean": { "node_id": "candidate_07cf9b9e2ef0417e1afc", "mean_train_ce": 1.3868277808651328, "mean_test_ce": 1.3867692332714796 }, "coordinate_mean": { "node_id": "candidate_c65bf21470c8b1e81842", "mean_train_ce": 0.29576607677154243, "mean_test_ce": 0.3118247539969161 }, "spatial": { "node_id": 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periods", "judgment": "overstated", "assessment": "局部梯度/二阶结构也可携带方向，不存在至少数个周期的普遍必要条件；有限CNN学不动不证明表示上做不到。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "The coarse 6×6 map and 4-px patches discard more fine oscillation detail", "judgment": "plausible_unmeasured", "assessment": "投影是学习式多通道，输出保留哪些特征未直接测量；stride4实际train/test近零，完整控制支持尺度/优化关联而不是必然丢方向信息。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ 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"data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "6e77b5743535712c7642833bd3a0ff953bd395ac777b791a215d62cedbd76db7", "probe": null, "instance_id": "learning_rate_s841901", "actual_comparison_evidence": { "lr1e4": { "node_id": "candidate_31abb7f5ae858e9f35e8", "mean_train_ce": 1.3848290643654764, "mean_test_ce": 1.3849183171987534 }, "lr1e3": { "node_id": "candidate_6ec59d4186f9b42d6754", "mean_train_ce": 0.5936531231127447, "mean_test_ce": 0.6058920508075971 }, "lr1e2": { "node_id": "candidate_b07779969f06e2a919a4", "mean_train_ce": 0.2570996006147652, "mean_test_ce": 0.2773895292477846 } }, "public_fields_reviewed": [ "content", "explanation" ], "comparison_coverage_note": "已核对两条相邻关系及实际字母映射；此字段评价覆盖范围，不等同于关系预测正确。", "answer_consistency_note": "正文的最终比较主张与本条提交顺序一致；跨主问题/字母重排变化由单独permutation统计处理。" }, { "question_id": "q_ccb7af737a4a7277553ef9ecb8d05e6b", "model": "claude-haiku-5-5", "ranking_correct": false, "summary_zh": "认识到欠学习与高LR风险但把常用默认值当最优，参数量也低报；完整train/test不支持过拟合主导排序。", "scores": { "code_fidelity": "partly_supported", "mechanism_alignment": "partly_supported", "causal_calibration": "partly_supported", "comparison_coverage": "supported", "answer_consistency": "supported" }, "annotations": [ { "verbatim_public_quote": "about a few thousand parameters", "judgment": "incorrect", "assessment": "该mean CNN实际15436参数；这一规模描述不准确。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" }, { "verbatim_public_quote": "C (1e-2) is probably worst: the high learning rate risks overfitting", "judgment": "plausible_unmeasured", "assessment": "实际0.01完整train/test均更低，且差值较小；不能用风险替代真实泛化证据。回答使用probably/risk，故不把风险本身判作逻辑不可能。", "evidence_path": "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/control_audit.json", "additional_evidence_paths": [ "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/resolved_plan.json", "data/task_expansion/vision_batch/image_ranking_v1_20261015/classification/quality_analysis/classification_quality.json" ], "scope_limit": "当前固定合成数据、候选与有限训练预算；局部对照为描述性机制证据。正确或错误排序本身不证明/反证唯一机制；没有读取隐藏推理。" } ], "response_sha256": "605f8e049d43fa2da327b86f6d54bd902d3370b6caaca5cde5b152963d0c43e3", "probe": { "type": 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