{"id":"W3162112911","doi":"10.7202/1076994ar","title":"Le livre numérique : quelques millions de prêts plus tard","year":2021,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Education, sociology, and vocational training","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Humanities; Political science; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008869755,0.0003339967,0.0005619903,0.001635544,0.003652079,0.002655272,0.0007627266,0.0007460614,0.03458765],"category_scores_gemma":[0.003112061,0.0002006905,0.0002030162,0.003575167,0.001371996,0.001649593,0.00137603,0.001875134,0.00438305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0131212,"about_ca_system_score_gemma":0.01768939,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8186726,"about_ca_topic_score_gemma":0.9162007,"domain_scores_codex":[0.9991285,0.00008940972,0.0000264925,0.00009422848,0.0003754577,0.0002860497],"domain_scores_gemma":[0.9980131,0.0001579874,0.0002011018,0.00006453939,0.0007647825,0.0007985371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002607048,0.0001021321,0.1023777,0.0008807908,0.00005452488,0.0009291536,0.02535781,0.0002817671,0.001202038,0.0440069,0.3150157,0.5095309],"study_design_scores_gemma":[0.00001425422,0.00007422215,0.223883,0.0006404488,0.00001484106,0.0003849663,0.01499784,0.000205449,0.0001716967,0.001433224,0.7581451,0.00003495023],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6078952,0.05373094,0.002159874,0.09040526,0.00249849,0.0001504575,0.01424354,0.0004112885,0.2285049],"genre_scores_gemma":[0.5820057,0.02295579,0.0009884136,0.004049619,0.0005778171,0.0001235489,0.004262804,0.0001713418,0.384865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9973447,"threshold_uncertainty_score":0.3647905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114876373076936,"score_gpt":0.4540655456412616,"score_spread":0.342577908333568,"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."}}