{"id":"W7097493298","doi":"","title":"Acquisitions and Acquisitions et Bibliographie Services services bibliographiques","year":2001,"lang":"en","type":"article","venue":"","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Legislation; Order (exchange); National library; Subject (documents)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00270583,0.001039232,0.001164541,0.01719237,0.002713336,0.01486116,0.001166532,0.001711972,0.5162227],"category_scores_gemma":[0.01279168,0.0007625126,0.0005720456,0.04090902,0.0008139815,0.005181851,0.002524721,0.001531431,0.4499794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007288063,"about_ca_system_score_gemma":0.01668814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06080004,"about_ca_topic_score_gemma":0.03977245,"domain_scores_codex":[0.9949103,0.0007017114,0.0006060604,0.0005942401,0.00274643,0.0004412229],"domain_scores_gemma":[0.9922454,0.0009100288,0.0007599639,0.001186742,0.004023146,0.0008748099],"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":[0.00005183822,0.00002198567,0.0009826658,0.000474663,0.00001261515,0.00004795166,0.0002231322,0.00009385828,0.0004502487,0.0206741,0.810473,0.166494],"study_design_scores_gemma":[0.000003858281,0.000003170044,0.000919039,0.00005892949,0.000002304315,0.00003249055,0.00006837837,0.00003829104,0.0001121764,0.0004028465,0.9983528,0.000005815466],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001562022,0.006116202,0.00245024,0.004832211,0.002010753,0.0003548041,0.0646804,0.004520053,0.9134734],"genre_scores_gemma":[0.009669666,0.01030819,0.003654256,0.0006317935,0.0008915831,0.0002705902,0.05391388,0.002282144,0.9183779],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5162227,"threshold_uncertainty_score":0.6900496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01007787268931561,"score_gpt":0.2444634326919921,"score_spread":0.2343855600026765,"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."}}