{"id":"W6949403698","doi":"10.5281/zenodo.14827754","title":"Explorer les REL : comment libérer pour mieux partager","year":2025,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Western europe; Public policy; Nature Conservation; Poison control","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","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001149821,0.0002396934,0.0002179539,0.0003219639,0.003630322,0.003172001,0.002135087,0.0001280783,0.02210747],"category_scores_gemma":[0.0008074765,0.0002738702,0.00009930988,0.001147603,0.0002387456,0.0008080318,0.002879565,0.0006838173,0.02666943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002908313,"about_ca_system_score_gemma":0.00003016627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006258609,"about_ca_topic_score_gemma":5.430922e-7,"domain_scores_codex":[0.9968041,0.001040162,0.0004159719,0.000687759,0.0004165948,0.0006354209],"domain_scores_gemma":[0.9978614,0.00008124123,0.0001481785,0.0007835275,0.0008503045,0.0002752943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001630346,0.0003041102,0.00002417426,0.00008146132,0.0000508356,0.00001131323,0.00430325,0.0001146558,0.000214825,0.1668996,0.6857479,0.1422317],"study_design_scores_gemma":[0.0005262095,0.0001275783,0.001555517,0.0001878786,0.00002282956,0.00003904723,0.003285529,0.003351137,0.0003414891,0.0007054732,0.9895961,0.0002612482],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005456165,0.001318835,0.04540662,0.2401171,0.002174156,0.0007479925,0.00005291784,0.001770672,0.7029555],"genre_scores_gemma":[0.6864785,0.001644843,0.007123509,0.009982796,0.0008993067,4.925847e-7,0.001024802,0.00308117,0.2897646],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6810223,"threshold_uncertainty_score":0.9999713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07362754234159441,"score_gpt":0.2899561798111657,"score_spread":0.2163286374695713,"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."}}