{"id":"W1497038371","doi":"","title":"Enseigner la morphologie dérivationnelle pour apprendre l’orthographe lexicale","year":2014,"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 du Québec à Montréal","funders":"","keywords":"Linguistics; Philosophy","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":[0.001906508,0.0003025355,0.0003654645,0.0001993617,0.001421862,0.00004691976,0.0006267147,0.0005634798,0.002285687],"category_scores_gemma":[0.0008603049,0.0003515026,0.0003089897,0.0009954339,0.0008048207,0.0002655281,0.00028759,0.0006483837,0.0005849028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001997658,"about_ca_system_score_gemma":0.0000984349,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0138726,"about_ca_topic_score_gemma":0.02082671,"domain_scores_codex":[0.9951476,0.002803062,0.0002245973,0.0005611042,0.0004544107,0.0008092322],"domain_scores_gemma":[0.9974242,0.001343885,0.0002429408,0.0005031789,0.0001194049,0.0003663267],"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":[0.00004004436,0.0002032199,0.003456962,0.00004571443,0.0001320799,0.0009730172,0.008837169,0.001546648,0.001398672,0.2752427,0.2083078,0.4998161],"study_design_scores_gemma":[0.0006546048,0.0000915238,0.002826642,0.0000515795,0.0001320769,0.0001041554,0.005176276,0.001827715,0.0001522378,0.007907611,0.9806688,0.0004067839],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.3267848,0.08413998,0.08596573,0.1289155,0.002019234,0.0004876866,0.0000459705,0.0006765498,0.3709645],"genre_scores_gemma":[0.2910277,0.004431839,0.05771525,0.0007825074,0.0009525086,0.000009502549,0.00003346044,0.00006889964,0.6449783],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.772361,"threshold_uncertainty_score":0.9998937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162650789778027,"score_gpt":0.2118346638832875,"score_spread":0.2002081559855072,"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."}}