{"id":"W36161844","doi":"10.1136/bmjophth-2021-000914","title":"k-tablet Structures and Crossover on Latent Variables for Real-Coded GA.","year":2002,"lang":"en","type":"article","venue":"BMJ Open Ophthalmology","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Crossover; Latent variable; Computer science; Statistics; Mathematics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002780712,0.0001323966,0.0002186917,0.00004532157,0.0002426584,0.0004053377,0.001098172,0.00008665387,0.000183316],"category_scores_gemma":[0.0000598695,0.0001127335,0.0000253478,0.0001314948,0.00006446852,0.0002988584,0.000631811,0.00007538405,0.00003718373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001661831,"about_ca_system_score_gemma":0.00002338179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002467896,"about_ca_topic_score_gemma":0.000001876616,"domain_scores_codex":[0.9988573,0.00004265225,0.0002060201,0.0005148645,0.00009535791,0.0002837941],"domain_scores_gemma":[0.9988611,0.0001980708,0.0001092361,0.0007022521,0.0000497352,0.00007957188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008105509,0.0003077887,0.001079207,0.00004437405,0.00008194993,0.0001478599,0.0005799973,0.0002523441,0.0005784337,0.8592745,0.09184328,0.04572919],"study_design_scores_gemma":[0.007736739,0.00272456,0.08307477,0.0001232388,0.00007019317,0.008687622,0.00009823377,0.499282,0.002495121,0.2684772,0.1251629,0.002067449],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.476688,0.0005013114,0.2107664,0.02761239,0.002980761,0.01679076,0.001461158,0.0005285384,0.2626707],"genre_scores_gemma":[0.5033129,0.00004110417,0.4800579,0.001060653,0.0002214432,0.001564643,0.00008099634,0.00003807151,0.01362232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5907973,"threshold_uncertainty_score":0.4597137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1071735256820817,"score_gpt":0.3774060266018782,"score_spread":0.2702325009197964,"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."}}