{"id":"W6911763726","doi":"10.5281/zenodo.13349673","title":"L'IA comme complice du formateur","year":2024,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Artificial Intelligence in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Work (physics); Subject (documents); Initial training","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":[0.002641903,0.001313354,0.0006026559,0.00157603,0.001568909,0.007245199,0.001484838,0.002128704,0.05558849],"category_scores_gemma":[0.01051864,0.0005878746,0.001130767,0.001539623,0.002854037,0.005975259,0.002387749,0.003372084,0.01856878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001706772,"about_ca_system_score_gemma":0.00192283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004282554,"about_ca_topic_score_gemma":0.003088422,"domain_scores_codex":[0.9968908,0.0009972283,0.0002029983,0.0006093431,0.001017192,0.0002824414],"domain_scores_gemma":[0.9936485,0.002185281,0.0002734017,0.001797081,0.001898835,0.0001970328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002791445,0.00007740821,0.00117033,0.0004381098,0.00003667867,0.001114837,0.003818382,0.002805217,0.008659762,0.7857807,0.04562518,0.1501943],"study_design_scores_gemma":[0.00003024582,0.0001126967,0.0004755149,0.000269106,0.00002779338,0.001780878,0.0007832192,0.006331789,0.01123335,0.0410093,0.9378917,0.00005451938],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01512989,0.002088437,0.614448,0.004292279,0.005299903,0.0004045726,0.001279437,0.006662311,0.3503953],"genre_scores_gemma":[0.2180908,0.002928557,0.3280523,0.002945262,0.001872016,0.0006294531,0.002489863,0.004248485,0.4387433],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05558849,"threshold_uncertainty_score":0.185962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1390634797547974,"score_gpt":0.3313046771561252,"score_spread":0.1922411974013278,"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."}}