{"id":"W6912428751","doi":"10.5281/zenodo.3249188","title":"matbesancon/BilevelOptimization.jl: v0.2.1","year":2019,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Bilevel optimization; Toolbox; Process (computing); Selection (genetic algorithm); Sketch","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":[0.0013405,0.002838628,0.001667529,0.00148817,0.0005424028,0.003037348,0.003065006,0.002321762,0.2406958],"category_scores_gemma":[0.003168686,0.001370286,0.001524569,0.001411254,0.001119549,0.001955174,0.003362363,0.003596783,0.1660605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009070954,"about_ca_system_score_gemma":0.001433938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002674225,"about_ca_topic_score_gemma":0.003514443,"domain_scores_codex":[0.99927,0.0001204338,0.00004342682,0.0001493351,0.0002932329,0.000123426],"domain_scores_gemma":[0.9993554,0.0002182703,0.00005178172,0.0001573869,0.0001476284,0.00006953382],"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":[0.0004934834,0.000223843,0.0005446156,0.001978425,0.0001636351,0.000255791,0.0002020521,0.06102257,0.008333964,0.1100646,0.5363176,0.2803993],"study_design_scores_gemma":[0.0004751706,0.00009338657,0.0003336357,0.0004087687,0.00004786378,0.0002841847,0.00004592575,0.3541634,0.01470826,0.106791,0.5225211,0.0001272974],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00134539,0.0009593786,0.7067896,0.0004954214,0.0003118151,0.0001570759,0.01109677,0.2170841,0.06176056],"genre_scores_gemma":[0.06583305,0.001851458,0.578843,0.001064648,0.0002714324,0.001250565,0.03658718,0.2125435,0.1017553],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2406958,"threshold_uncertainty_score":0.8052076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03321316067621267,"score_gpt":0.2434138018314338,"score_spread":0.2102006411552211,"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."}}