{"id":"W3007116216","doi":"10.1145/3365953.3365955","title":"<i>BENIN</i>","year":2019,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Inference; Computer science; Benchmark (surveying); Resampling; Machine learning; Artificial intelligence; Feature selection; Complementarity (molecular biology); Data mining; Gene regulatory network; Gene expression; Gene; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002005605,0.001186571,0.001003383,0.001540784,0.0008424561,0.002073713,0.002169,0.001866749,0.008161828],"category_scores_gemma":[0.008391064,0.0004844005,0.0007237666,0.002017544,0.001069461,0.002469515,0.001874895,0.003235174,0.007873171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007195765,"about_ca_system_score_gemma":0.0007837733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004429316,"about_ca_topic_score_gemma":0.006797532,"domain_scores_codex":[0.9988753,0.0003094726,0.00004583934,0.0002955088,0.0004142055,0.00005963134],"domain_scores_gemma":[0.9966614,0.001538658,0.0002122693,0.0006282346,0.0006985606,0.0002608312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000279402,0.0001520021,0.00332306,0.0003953188,0.0001669001,0.0002134842,0.00009385912,0.04098431,0.006857921,0.02381269,0.5643987,0.3593224],"study_design_scores_gemma":[0.00006956956,0.000166893,0.003886109,0.0001579602,0.00007092892,0.0006218757,0.00009317875,0.509783,0.02474983,0.09801839,0.3622025,0.0001798191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01453173,0.008679884,0.8898125,0.04036503,0.005908744,0.0001753458,0.006342704,0.01517463,0.01900941],"genre_scores_gemma":[0.2006209,0.00945033,0.6959733,0.01681443,0.008630285,0.0006162944,0.02664376,0.007080161,0.03417042],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9918382,"threshold_uncertainty_score":0.02730399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006178601518985226,"score_gpt":0.2117773907233556,"score_spread":0.2055987892043704,"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."}}