{"id":"W1673923490","doi":"10.48550/arxiv.1312.6199","title":"Intriguing properties of neural networks","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5745,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Artificial neural network; Artifact (error); Perturbation (astronomy); Artificial intelligence; Deep neural networks; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002174663,0.0005454027,0.0006522624,0.001131281,0.00101132,0.002569102,0.001123712,0.002028613,0.004143829],"category_scores_gemma":[0.01758193,0.0005158365,0.0006224852,0.0006068708,0.003783608,0.005455392,0.001948006,0.003370179,0.0005411797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008574,"about_ca_system_score_gemma":0.0004997265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001129676,"about_ca_topic_score_gemma":0.0008092194,"domain_scores_codex":[0.9986798,0.0003958086,0.00007366498,0.0003382894,0.000405142,0.0001072926],"domain_scores_gemma":[0.9950073,0.003171466,0.0003764799,0.0007370085,0.0005191842,0.0001885917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006678484,0.00002830509,0.00201758,0.0001565733,0.0000746353,0.00014764,0.0002006288,0.04174177,0.002813379,0.9201477,0.003273973,0.02933107],"study_design_scores_gemma":[0.00001636185,0.00002560902,0.0007467676,0.00003504981,0.00001512459,0.0001385751,0.00003863982,0.09786592,0.0007021729,0.8958808,0.004520046,0.00001498526],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1652298,0.01006788,0.705673,0.02419975,0.0009476927,0.0001153264,0.001149493,0.001015694,0.09160152],"genre_scores_gemma":[0.9397686,0.003517862,0.04620017,0.001327805,0.001026795,0.0001879004,0.0003802492,0.0001788316,0.007412015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004143829,"threshold_uncertainty_score":0.01386249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07728990108899962,"score_gpt":0.1701870991943954,"score_spread":0.0928971981053958,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}