{"id":"W2766196653","doi":"10.1142/11784","title":"Generalization with Deep Learning","year":2020,"lang":"en","type":"book","venue":"WORLD SCIENTIFIC eBooks","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":182,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Office; Air Force Office of Scientific Research; Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Generalization; Maxima and minima; Computer science; Deep learning; Artificial intelligence; Deep neural networks; Theoretical computer science; Machine learning; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004352353,0.001399546,0.001282827,0.001840083,0.0008695662,0.00264495,0.0025136,0.001626038,0.007457685],"category_scores_gemma":[0.01499234,0.0006907926,0.001790304,0.001496742,0.003492631,0.00841291,0.005432256,0.006151753,0.001406027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003087305,"about_ca_system_score_gemma":0.001236118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001814673,"about_ca_topic_score_gemma":0.001383579,"domain_scores_codex":[0.9971803,0.0007256671,0.0001492516,0.0006560702,0.001086498,0.0002020703],"domain_scores_gemma":[0.9950222,0.002832716,0.0002906726,0.001239774,0.0004650949,0.0001495181],"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":[0.00003397996,0.00002083311,0.0003780887,0.0002285221,0.00005841219,0.00004947092,0.0000764886,0.05663451,0.0009055267,0.8755525,0.00955737,0.05650418],"study_design_scores_gemma":[0.000005215924,0.00002291556,0.0001720559,0.00005677472,0.00001358652,0.00006308101,0.00001473031,0.1062086,0.0004958728,0.8832449,0.009691142,0.00001102385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.009298476,0.006509096,0.9274663,0.00482308,0.0005545801,0.00006402992,0.0003638584,0.0006217937,0.05029877],"genre_scores_gemma":[0.6368071,0.01243086,0.3073737,0.005538608,0.002724898,0.0006110622,0.001186838,0.0009008651,0.0324261],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007457685,"threshold_uncertainty_score":0.02494842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01527863187937388,"score_gpt":0.2106973804975417,"score_spread":0.1954187486181678,"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."}}