{"id":"W2799756024","doi":"10.20383/101.033","title":"Expenditures of CARL member libraries for scholarly resource subscriptions licensed through CRKN for 2016 - 2017 / Dépenses des bibliothèques membres de l'ABRC pour les abonnements aux ressources savantes sous licence du RCDR pour l'année 2016 - 2017","year":2018,"lang":"fr","type":"article","venue":"Open MIND","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"License; Library science; Political science; Documentation; Computer science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001751347,0.0006629314,0.0008703855,0.0007520184,0.003068515,0.0146222,0.005398245,0.000412939,0.001238019],"category_scores_gemma":[0.001052059,0.0005645555,0.0003592421,0.0009511102,0.00220945,0.06484816,0.001200493,0.0002601953,0.0005047458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000757448,"about_ca_system_score_gemma":0.002174737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00157259,"about_ca_topic_score_gemma":0.0003335763,"domain_scores_codex":[0.994902,0.0004100268,0.001476437,0.001102937,0.0007740395,0.00133452],"domain_scores_gemma":[0.9942303,0.00130907,0.001417896,0.001351463,0.001292707,0.0003985728],"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":[0.0004622188,0.0003771685,0.008161543,0.0002943632,0.0002341919,0.00001058589,0.08734539,0.00006960434,0.01196896,0.005758461,0.8787025,0.006615056],"study_design_scores_gemma":[0.001929885,0.0009238895,0.003385445,0.002002676,0.00007724726,0.0001010311,0.0242028,0.004311796,0.1346811,0.003944648,0.8235652,0.0008742834],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7506737,0.02765868,0.1208406,0.02078892,0.004003482,0.006333692,0.002285574,0.0001460015,0.06726936],"genre_scores_gemma":[0.5633821,0.003510732,0.271706,0.00179961,0.003632119,0.0005832983,0.0001437789,0.000130055,0.1551124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1872916,"threshold_uncertainty_score":0.999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1719817526546069,"score_gpt":0.3520656367062645,"score_spread":0.1800838840516576,"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."}}