{"id":"W2594153243","doi":"10.6000/1929-6029.2017.06.01.1","title":"Evaluation of Methods for Gene Selection in Melanoma Cell Lines","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"African Union","keywords":"Selection (genetic algorithm); DNA microarray; Microarray analysis techniques; Computational biology; Melanoma; Biology; Computer science; Gene; Genetics; Gene expression; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0107333,0.00004445415,0.00009585316,0.0003256722,0.00001118534,0.000007449295,0.0002939697,0.0001008222,0.0001253738],"category_scores_gemma":[0.01034453,0.0000317328,0.00002999562,0.0001173115,0.00007588736,0.000005720606,0.00004507705,0.0001323367,6.776341e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001302938,"about_ca_system_score_gemma":0.0008605984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001294523,"about_ca_topic_score_gemma":0.00004103599,"domain_scores_codex":[0.9973269,0.0006261169,0.0004618707,0.000117679,0.001352216,0.00011519],"domain_scores_gemma":[0.9960787,0.0004393061,0.0001670084,0.00005591716,0.003194932,0.00006418682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002343047,0.0001070873,0.0012992,0.000007025341,0.00001771446,0.000001491137,0.0000257294,0.00004195147,0.6104813,0.0004092687,0.001581428,0.3857935],"study_design_scores_gemma":[0.004475954,0.0006086532,0.01664665,0.0002118315,0.0000134032,0.00002252951,0.0001083634,0.009429323,0.9369916,0.01591609,0.01549028,0.00008535286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2464613,0.0006307087,0.7510967,0.0009514421,0.0003913716,0.0001608054,0.00002933394,5.997893e-7,0.0002776847],"genre_scores_gemma":[0.9521207,0.00131707,0.04609254,0.00002465394,0.0002968598,0.00002446777,0.00001068479,0.000006988193,0.0001060053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7056594,"threshold_uncertainty_score":0.9979917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1320632548069261,"score_gpt":0.5555952952535591,"score_spread":0.423532040446633,"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."}}