{"id":"W2938038604","doi":"10.3819/ccbr.2019.140011","title":"Probability Learning by Perceptrons and People","year":2022,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perceptron; Margin (machine learning); White (mutation); Animal learning; Psychology; Artificial intelligence; Mathematics education; Cognitive psychology; Computer science; Machine learning; Biology; Artificial neural network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.004283103,0.0007977129,0.0009190383,0.001324332,0.0005927887,0.003645677,0.00124557,0.001923393,0.01177464],"category_scores_gemma":[0.02085877,0.0007261674,0.00113052,0.001070987,0.003028954,0.006706083,0.001673629,0.003302973,0.002372011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001618887,"about_ca_system_score_gemma":0.0008265848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003754108,"about_ca_topic_score_gemma":0.002464661,"domain_scores_codex":[0.9981303,0.0009648378,0.00007669324,0.000461707,0.0002354165,0.0001310212],"domain_scores_gemma":[0.9916071,0.00635619,0.0004254919,0.0006819977,0.000599061,0.0003301944],"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":[0.0002365578,0.0001200881,0.004536654,0.0003609925,0.0003037002,0.0001014763,0.0003504381,0.1013707,0.0004467528,0.7347605,0.02344316,0.133969],"study_design_scores_gemma":[0.00002896994,0.00003322494,0.0007492352,0.00007927886,0.00002723382,0.00004724995,0.00004002669,0.2084959,0.0003165504,0.7849856,0.005171039,0.00002569036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0393239,0.009029954,0.8662913,0.02144048,0.001265728,0.00008339903,0.000668142,0.00142537,0.06047171],"genre_scores_gemma":[0.8423874,0.006918525,0.1121121,0.002096057,0.001495293,0.000198647,0.000778484,0.0004114602,0.03360221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01177464,"threshold_uncertainty_score":0.03939009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1226079152482652,"score_gpt":0.3369039865798235,"score_spread":0.2142960713315583,"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."}}