{"id":"W2980166406","doi":"10.20383/101.0187","title":"Expenditures of CARL member libraries for scholarly resource subscriptions licensed through CRKN for 2018 - 2019 / Dépenses des bibliothèques membres de l'ABRC pour les abonnements aux ressources savantes sous licence du RCDR pour l'année 2018 - 2019","year":2019,"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001933079,0.0006738892,0.001165906,0.01679348,0.001767154,0.004114517,0.001779195,0.0007370074,0.05476834],"category_scores_gemma":[0.02006306,0.0005944621,0.0008716899,0.04712996,0.0003298378,0.002132635,0.001786463,0.001291736,0.02099808],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01692714,"about_ca_system_score_gemma":0.03530456,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8868015,"about_ca_topic_score_gemma":0.9232257,"domain_scores_codex":[0.9954788,0.0002433441,0.0005189751,0.0005035645,0.00261808,0.0006373126],"domain_scores_gemma":[0.9702446,0.0032077,0.003178515,0.001076322,0.02003236,0.002260459],"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":[0.0001203108,0.00001752976,0.02013791,0.0007844998,0.00009439691,0.00003431477,0.0001874632,0.00031651,0.00008936979,0.001424168,0.9631044,0.013689],"study_design_scores_gemma":[0.00004996398,0.0000129309,0.1349238,0.0006696471,0.0001035614,0.00008442908,0.001484615,0.0003602756,0.0004170057,0.0003415786,0.8614729,0.00007930509],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.002016833,0.0003650782,0.00004887912,0.0003545955,0.00003228113,0.00001872357,0.9910601,0.0001347999,0.005968734],"genre_scores_gemma":[0.01114899,0.001510837,0.0004185907,0.000180093,0.00004629399,0.00009567314,0.9691638,0.00009756765,0.01733818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9958855,"threshold_uncertainty_score":0.2277303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.110708895456899,"score_gpt":0.3225373162118195,"score_spread":0.2118284207549205,"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."}}