{"id":"W361002670","doi":"","title":"Différencier l’accompagnement en lecture par le texte incitatif","year":2006,"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 Sherbrooke","funders":"","keywords":"Art","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00101645,0.0003560062,0.0004010022,0.0001809944,0.001563172,0.00005800114,0.0006316968,0.0004255613,0.001862253],"category_scores_gemma":[0.00016454,0.0004197595,0.000259777,0.0009227522,0.0005208176,0.0003128285,0.0002906595,0.0005370866,0.0004027131],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006420463,"about_ca_system_score_gemma":0.000315976,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1815346,"about_ca_topic_score_gemma":0.4995772,"domain_scores_codex":[0.9962435,0.001310643,0.0002615559,0.0005554137,0.0006162325,0.00101268],"domain_scores_gemma":[0.998439,0.0004757068,0.0002602034,0.0004203141,0.0001118589,0.0002929201],"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":[0.0000542197,0.0004183915,0.006235435,0.00008228129,0.0001874084,0.002364424,0.01586068,0.004967028,0.002987204,0.1697892,0.2504748,0.546579],"study_design_scores_gemma":[0.0007529468,0.00008795068,0.01589667,0.00005715739,0.0001479063,0.00006848229,0.002829991,0.0007226277,0.000230585,0.006039284,0.9726987,0.000467644],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4710911,0.2482994,0.01338699,0.1390458,0.001705644,0.0005940291,0.0000538469,0.0003370579,0.1254862],"genre_scores_gemma":[0.42482,0.002362509,0.03291747,0.0007874948,0.001240942,0.000009316163,0.00004920248,0.00007065277,0.5377424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.722224,"threshold_uncertainty_score":0.9998254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005137645056915173,"score_gpt":0.1926813816402636,"score_spread":0.1875437365833484,"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."}}