{"id":"W6967046959","doi":"10.48782/e-jiref-10-2-71","title":"La fidélité des scores totaux et la fidélité des scores logits : le cas du modèle de Rasch","year":2024,"lang":"fr","type":"peer-review","venue":"Association pour le Développement des Méthodologies d’Évaluation en Éducation - Europe","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université de Montréal","funders":"","keywords":"Rasch model; Context (archaeology); Measure (data warehouse); Definiteness","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1289404,0.001939112,0.003411268,0.004288444,0.001885806,0.009131365,0.0032292,0.002215511,0.01055271],"category_scores_gemma":[0.3359973,0.001283734,0.005101171,0.00543241,0.008151837,0.006984858,0.005170431,0.006492433,0.002657994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003296789,"about_ca_system_score_gemma":0.005777359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01408232,"about_ca_topic_score_gemma":0.01090652,"domain_scores_codex":[0.8473653,0.1177907,0.003700922,0.01324965,0.01492199,0.002971462],"domain_scores_gemma":[0.5187165,0.4183506,0.01300208,0.03134209,0.016988,0.001600725],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00202888,0.0002781309,0.227053,0.001115478,0.004924406,0.0004730205,0.009228939,0.08601052,0.001109681,0.3366751,0.006607821,0.324495],"study_design_scores_gemma":[0.0002718934,0.001418348,0.1368946,0.001150066,0.001664307,0.001283987,0.004314966,0.3570796,0.003267016,0.4546314,0.037347,0.0006767555],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2039257,0.002335908,0.7684192,0.005315199,0.0005020699,0.0006962339,0.001269292,0.0008569355,0.01667948],"genre_scores_gemma":[0.8913139,0.0009782872,0.09369804,0.0006095457,0.0002658093,0.00110822,0.000901571,0.0002958114,0.0108288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8710595,"threshold_uncertainty_score":0.6819103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2787726954257982,"score_gpt":0.4089917961084948,"score_spread":0.1302191006826966,"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."}}