{"id":"W3015333924","doi":"10.1145/3377930.3390226","title":"GeneCAI","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Office; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Computer science; Hyperparameter; Scalability; Pareto principle; Artificial intelligence; Multi-objective optimization; Machine learning; Mathematical optimization","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001500212,0.001621315,0.00155657,0.001511274,0.001009309,0.002789463,0.003639638,0.002245786,0.03774763],"category_scores_gemma":[0.004613109,0.0005885187,0.001450426,0.001757621,0.0008343514,0.002014737,0.002092823,0.003704575,0.01693681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001790746,"about_ca_system_score_gemma":0.003202852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009859352,"about_ca_topic_score_gemma":0.009819441,"domain_scores_codex":[0.9989228,0.0001751653,0.0000638136,0.0003149931,0.0004100108,0.0001131741],"domain_scores_gemma":[0.9989946,0.0002795664,0.00005529392,0.0002661565,0.0003167805,0.00008759701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004573542,0.0001611762,0.001056479,0.0005152615,0.0002622411,0.0001801846,0.00009036616,0.0849094,0.003223128,0.0660007,0.3249019,0.5182419],"study_design_scores_gemma":[0.0002262528,0.0001102672,0.0005767067,0.0001032699,0.0000682124,0.0002094348,0.00003282494,0.6580576,0.006219423,0.09511797,0.2391998,0.00007826515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00903215,0.007990721,0.8252138,0.003857144,0.003715244,0.0005621983,0.005583175,0.06478073,0.07926486],"genre_scores_gemma":[0.1592761,0.006285921,0.7009758,0.004095155,0.001345688,0.002232233,0.02719741,0.01201525,0.08657646],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03774763,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05057353322850214,"score_gpt":0.2905393398512218,"score_spread":0.2399658066227197,"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."}}