{"id":"W4395101197","doi":"10.7202/1110339ar","title":"Météos du comportement : outils de gestion de classe ou « provocateurs de déviance » ?","year":2023,"lang":"fr","type":"article","venue":"Revue des sciences de l éducation","topic":"Bullying, Victimization, and Aggression","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deviance (statistics); Psychology; Environmental science; Meteorology; Computer science; Geography; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002563682,0.0003271698,0.000516559,0.001247368,0.002039499,0.005035906,0.0008555985,0.001858015,0.01115096],"category_scores_gemma":[0.01651321,0.0003006975,0.0003454351,0.001069074,0.009509919,0.006170741,0.003272787,0.003502192,0.0009588936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002481297,"about_ca_system_score_gemma":0.001787961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009101571,"about_ca_topic_score_gemma":0.009569584,"domain_scores_codex":[0.9961787,0.001995436,0.0001762208,0.000336602,0.0007840754,0.000528816],"domain_scores_gemma":[0.9917682,0.003952072,0.00225068,0.0004329533,0.0007383804,0.0008576209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0007551617,0.0002510996,0.08716537,0.001093703,0.0001102933,0.0009920262,0.08762217,0.0003423827,0.001516885,0.5100272,0.03850023,0.2716234],"study_design_scores_gemma":[0.00007881462,0.0003565305,0.3458024,0.004716697,0.0001230238,0.003240262,0.1467154,0.0005892406,0.001435613,0.1632093,0.3334855,0.000247231],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.414479,0.1591132,0.0095623,0.135795,0.004732799,0.0001275207,0.001012633,0.0001080333,0.2750695],"genre_scores_gemma":[0.9639372,0.02099738,0.0008555762,0.001652893,0.0008533663,0.0000646337,0.0001352928,0.0000502433,0.01145345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01115096,"threshold_uncertainty_score":0.03730369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3314825682355542,"score_gpt":0.4349560915349894,"score_spread":0.1034735232994352,"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."}}