{"id":"W6929118331","doi":"10.4230/lipics.ccc.2023.12","title":"Improved Learning from Kolmogorov Complexity","year":2023,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Kolmogorov complexity; Boolean function; String (physics); Probably approximately correct learning; Function (biology); Circuit complexity; Relaxation (psychology); Boolean circuit","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":[0.003988994,0.001636273,0.002869985,0.002443132,0.001363158,0.003896756,0.003679128,0.002274857,0.009527376],"category_scores_gemma":[0.05150858,0.000948441,0.002062608,0.002539146,0.003108669,0.01257053,0.007367981,0.007508867,0.0018905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004485641,"about_ca_system_score_gemma":0.00267193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003045976,"about_ca_topic_score_gemma":0.003361476,"domain_scores_codex":[0.9946449,0.001543404,0.0002416213,0.001636883,0.0015077,0.0004254136],"domain_scores_gemma":[0.9614929,0.0290993,0.001157179,0.005407026,0.002161613,0.0006820583],"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":[0.0004863592,0.0002703304,0.00506297,0.000939192,0.0002085001,0.0001760108,0.0005498079,0.1607543,0.002648511,0.539673,0.02702351,0.2622075],"study_design_scores_gemma":[0.00004687166,0.00006903711,0.0007223162,0.00006302353,0.00003640152,0.0000578886,0.00002948961,0.442993,0.0008844747,0.5511226,0.003948613,0.00002630253],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04928631,0.00522436,0.908092,0.00599577,0.0005237038,0.0001859788,0.001311413,0.002789626,0.02659087],"genre_scores_gemma":[0.7370576,0.002971788,0.2351398,0.00271182,0.002053155,0.0006574743,0.003201587,0.0008975961,0.01530917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009527376,"threshold_uncertainty_score":0.03254575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03117531730396246,"score_gpt":0.2518167329530661,"score_spread":0.2206414156491037,"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."}}