{"id":"W1540903029","doi":"","title":"Différencier d’abord auprès de tous les élèves : un exemple en lecture","year":2015,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"French Language Learning Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université de Moncton","funders":"","keywords":"Geography","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":[0.003829555,0.00132576,0.001177355,0.000954961,0.002247021,0.004146667,0.00221973,0.003945881,0.006345424],"category_scores_gemma":[0.01673024,0.0006765443,0.001423362,0.0008155968,0.00188927,0.004080072,0.003626274,0.005054207,0.003137134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00179269,"about_ca_system_score_gemma":0.002099077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01991076,"about_ca_topic_score_gemma":0.02275237,"domain_scores_codex":[0.9939021,0.001621418,0.0002937012,0.001478709,0.002097272,0.0006067795],"domain_scores_gemma":[0.9922653,0.00452728,0.000322582,0.001007376,0.001448967,0.0004284446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002044608,0.0006783481,0.01985907,0.0005176126,0.0002179423,0.003887,0.01063759,0.04423086,0.05855978,0.09764515,0.01827191,0.7434502],"study_design_scores_gemma":[0.0004228655,0.001351248,0.01944377,0.0004377096,0.000499928,0.004136188,0.00862042,0.5349451,0.1457672,0.09201477,0.191825,0.0005358122],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1293013,0.001925676,0.833903,0.004677965,0.001338154,0.0002334326,0.0003203048,0.005034519,0.02326562],"genre_scores_gemma":[0.5014325,0.0006833526,0.4642741,0.0005678048,0.00031993,0.000123578,0.0003979351,0.0009926724,0.03120806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01991076,"threshold_uncertainty_score":0.0395897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307163514416808,"score_gpt":0.2212797854988678,"score_spread":0.2082081503546998,"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."}}