{"id":"W4394082051","doi":"10.6084/m9.figshare.21485874","title":"Dataset - variable selection","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts","funders":"","keywords":"Selection (genetic algorithm); Variable (mathematics); Feature selection; Computer science; Artificial intelligence; Mathematics","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":[0.003924902,0.003850988,0.002270533,0.004462386,0.001620748,0.002964324,0.00535193,0.00355376,0.04056701],"category_scores_gemma":[0.01603756,0.000714305,0.00361913,0.004948716,0.0007393538,0.001315644,0.002537528,0.003906862,0.04674362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001699132,"about_ca_system_score_gemma":0.003760679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0136901,"about_ca_topic_score_gemma":0.02480979,"domain_scores_codex":[0.9969831,0.0007030688,0.0003999533,0.001059349,0.0005330638,0.0003215429],"domain_scores_gemma":[0.9952592,0.001843307,0.0002466025,0.001085851,0.001306014,0.0002589168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002567997,0.000229959,0.003519147,0.001378602,0.0002255572,0.0001051885,0.00004397398,0.002291442,0.0003514321,0.0006884391,0.9737355,0.01717395],"study_design_scores_gemma":[0.001823401,0.0002589493,0.01402433,0.000947219,0.0003299541,0.0003933544,0.0003338565,0.01141384,0.002189806,0.005421096,0.9627016,0.0001625105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001925661,0.0003816898,0.001408593,0.0002296007,0.0002000263,0.0002872525,0.9925972,0.001828185,0.001141763],"genre_scores_gemma":[0.00210838,0.0001029612,0.003877881,0.0001055146,0.00002595611,0.001001125,0.9918203,0.0001380169,0.0008198585],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04056701,"threshold_uncertainty_score":0.1357102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04609292544505646,"score_gpt":0.2993425333155434,"score_spread":0.253249607870487,"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."}}