{"id":"W2059499379","doi":"10.1080/03081070290018056","title":"Statistical learning theory, model identification and system information content","year":2002,"lang":"en","type":"article","venue":"International Journal of General Systems","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Toronto Metropolitan University","funders":"","keywords":"Computer science; Statistical learning theory; Mathematical theory; Simple (philosophy); Expression (computer science); Statistical theory; Probability theory; Identification (biology); Statistical model; Information theory; Artificial intelligence; Algorithmic learning theory; Learning theory; Management science; Industrial engineering; Machine learning; Mathematics; Active learning (machine learning); Engineering; Support vector machine","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":[0.002224109,0.001124518,0.001446717,0.001889372,0.0005865515,0.003066777,0.001377985,0.001937294,0.002572484],"category_scores_gemma":[0.01118317,0.0005330147,0.0008682999,0.002324501,0.003705105,0.005002287,0.001910015,0.002218258,0.000533423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001992392,"about_ca_system_score_gemma":0.001341618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001664491,"about_ca_topic_score_gemma":0.0007492929,"domain_scores_codex":[0.9981533,0.0007273386,0.00008946448,0.0003000544,0.0006229159,0.0001069464],"domain_scores_gemma":[0.99427,0.004580273,0.0004267206,0.0003379071,0.0003207914,0.00006436407],"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":[0.00001707592,0.0000246515,0.0006046061,0.0002146905,0.00007780427,0.0001219357,0.000145354,0.1181498,0.0004183298,0.8498108,0.001888845,0.0285262],"study_design_scores_gemma":[0.000004805337,0.00001436423,0.0001694622,0.00003671292,0.00001317865,0.00005745466,0.00002296354,0.1418249,0.0002324585,0.8548084,0.002800755,0.000014561],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005988685,0.004101137,0.9770642,0.002097215,0.0001077731,0.00004302762,0.0001499389,0.0001757979,0.01027225],"genre_scores_gemma":[0.728687,0.01486928,0.2450178,0.001289516,0.001340852,0.0005743136,0.0006272215,0.0001825853,0.007411302],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003066777,"threshold_uncertainty_score":0.01445585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03248984344631063,"score_gpt":0.2473958668784426,"score_spread":0.2149060234321319,"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."}}