{"id":"W7070742003","doi":"","title":"Pratiques d’enseignement\\n au Canada et au Brésil intégrant les arts dans les sciences et technologies","year":2017,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"The arts; Human science; Limiting; Context (archaeology)","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":[0.006676922,0.0007364075,0.0006713476,0.002215264,0.02652863,0.01647033,0.002244886,0.003307361,0.01304353],"category_scores_gemma":[0.009223948,0.0005448553,0.0005074145,0.002491495,0.04084588,0.005744914,0.00816791,0.007434032,0.001522823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04978697,"about_ca_system_score_gemma":0.09376357,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7821804,"about_ca_topic_score_gemma":0.8640252,"domain_scores_codex":[0.990456,0.003759499,0.0001793412,0.001037988,0.002658155,0.001908989],"domain_scores_gemma":[0.990776,0.003300355,0.0005240849,0.0005953818,0.003109298,0.001694819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005046391,0.00003568735,0.00339868,0.0001519876,0.00001940717,0.0004891012,0.6000838,0.0004943514,0.001296145,0.3520958,0.007566539,0.03431803],"study_design_scores_gemma":[0.00001733664,0.00004626561,0.009070902,0.0007532442,0.00002901558,0.0002575662,0.4152503,0.0007231737,0.001024533,0.0383587,0.5343781,0.00009086642],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2847526,0.007844251,0.02669139,0.05505988,0.000555091,0.000193649,0.0001910025,0.0003879551,0.6243242],"genre_scores_gemma":[0.8822825,0.002896096,0.005396939,0.00180943,0.00005674819,0.00008004594,0.0000716697,0.0001537136,0.1072528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2178196,"threshold_uncertainty_score":0.4382047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007964435683887064,"score_gpt":0.2103292074650272,"score_spread":0.2023647717811401,"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."}}