{"id":"W2583189786","doi":"10.1007/b100989","title":"Algorithmic Learning Theory","year":2004,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Cognitive science; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001886712,0.0006405652,0.0006250851,0.0008326697,0.0004984296,0.0008173564,0.00535701,0.0004523342,0.00002774448],"category_scores_gemma":[0.0003430718,0.0005515707,0.0002043615,0.001404069,0.0009196494,0.0006928856,0.002016939,0.001740183,0.0001878772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001633144,"about_ca_system_score_gemma":0.004968297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000133572,"about_ca_topic_score_gemma":0.00002437668,"domain_scores_codex":[0.995337,0.0001707911,0.0004776486,0.001923571,0.001003291,0.001087715],"domain_scores_gemma":[0.9970403,0.0007981232,0.0003103377,0.001353289,0.000251334,0.0002466349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003923478,0.00005644315,0.00004753351,0.00005754372,0.0000147145,0.0002154,0.003906855,0.05284392,0.00003120729,0.05789565,0.00007859962,0.8848482],"study_design_scores_gemma":[0.0004905259,0.0003056478,0.0001416044,0.0005311095,0.00001111775,0.0002054179,3.989615e-7,0.2900416,0.0005913619,0.6928017,0.01378582,0.001093735],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001878219,0.00128958,0.9636734,0.0001861479,0.002738445,0.0003175588,0.000001042055,0.0004273709,0.03134767],"genre_scores_gemma":[0.07604103,0.0001856225,0.8827081,0.00276903,0.003932557,0.00004890422,0.00002132862,0.0001410814,0.0341524],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8837545,"threshold_uncertainty_score":0.9996936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009120299820187654,"score_gpt":0.2312141218747951,"score_spread":0.2220938220546075,"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."}}