{"id":"W2980619507","doi":"10.20383/101.0186","title":"Expenditures of CARL member libraries for scholarly resource subscriptions licensed through CRKN for 2017 - 2018 / Dépenses des bibliothèques membres de l'ABRC pour les abonnements aux ressources savantes sous licence du RCDR pour l'année 2017 - 2018","year":2019,"lang":"fr","type":"article","venue":"Federated Research Data Repository","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"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.004271443,0.000675517,0.0009182068,0.00131833,0.00612764,0.02252991,0.006954442,0.0006028339,0.0001639257],"category_scores_gemma":[0.002521556,0.0006029091,0.0002828843,0.001625662,0.002301006,0.07060306,0.002317666,0.0008644047,0.0001898293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002234168,"about_ca_system_score_gemma":0.003756948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003662635,"about_ca_topic_score_gemma":0.0002680875,"domain_scores_codex":[0.9909009,0.001613886,0.001702611,0.0017095,0.002062986,0.002010162],"domain_scores_gemma":[0.9895056,0.003212507,0.001069024,0.003095419,0.002566983,0.0005504743],"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":[0.000515216,0.0003829067,0.007581082,0.001154204,0.0002889088,0.00003454188,0.01426078,0.0001707035,0.05088488,0.004117494,0.9203516,0.0002576453],"study_design_scores_gemma":[0.002493928,0.001426632,0.005876946,0.002870249,0.00006447412,0.0004076879,0.03749907,0.04905966,0.1798766,0.001936474,0.7173454,0.001142944],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7277697,0.09374457,0.07566871,0.0219212,0.009328685,0.01139031,0.01060269,0.001213391,0.04836076],"genre_scores_gemma":[0.8117219,0.008509294,0.046249,0.001054422,0.004443415,0.0007611266,0.001732315,0.0002149953,0.1253136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2030063,"threshold_uncertainty_score":0.9996423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2820086136008243,"score_gpt":0.3856223927449813,"score_spread":0.103613779144157,"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."}}