{"id":"W7001704900","doi":"","title":"Le congrès annuel de la S.H.C.","year":2020,"lang":"fr","type":"article","venue":"Érudit documents and data repository (Érudit Consortium, University of Montreal)","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Economic shortage; Corporatization","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001240974,0.00116639,0.0005905888,0.0009719331,0.002588494,0.002746669,0.0009790484,0.001224102,0.2051038],"category_scores_gemma":[0.001925209,0.0003443067,0.00053424,0.0007539396,0.001017633,0.001360428,0.002755709,0.002007494,0.1055353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003866288,"about_ca_system_score_gemma":0.007510713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06284986,"about_ca_topic_score_gemma":0.1536733,"domain_scores_codex":[0.9992249,0.0001005904,0.00001911212,0.0001181266,0.0003345986,0.0002027103],"domain_scores_gemma":[0.998265,0.00007144694,0.00007109974,0.00008785409,0.0006725887,0.0008320972],"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":[0.00006198712,0.00001286789,0.0003796018,0.00007910388,0.000004764373,0.00006888262,0.0001906867,0.00007551731,0.0004257975,0.003685193,0.9688335,0.02618206],"study_design_scores_gemma":[0.000001180236,0.000005457998,0.0004425859,0.00002179292,5.249653e-7,0.0000131704,0.00004526283,0.00001374444,0.00005162418,0.0001064787,0.9992962,0.00000199229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.009680792,0.03996969,0.00297755,0.1105478,0.1500711,0.0003438364,0.01561404,0.001210302,0.6695848],"genre_scores_gemma":[0.007012348,0.004110261,0.0004173655,0.001705301,0.003368226,0.00005516911,0.001751027,0.0002711322,0.9813092],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2051038,"threshold_uncertainty_score":0.6861405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02125358397810843,"score_gpt":0.24694822680099,"score_spread":0.2256946428228815,"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."}}