{"id":"W2534784384","doi":"10.5703/1288284316259","title":"Acquisitions in a Nutshell","year":2016,"lang":"en","type":"article","venue":"","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Session (web analytics); Library science; Field (mathematics); Computer science; Management; Political science; World Wide Web; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003673942,0.0007466649,0.0006510786,0.001297241,0.003928749,0.01364196,0.001266451,0.003164175,0.05184036],"category_scores_gemma":[0.007202168,0.0007119743,0.0004492949,0.002454312,0.005887191,0.01968448,0.009955736,0.007130977,0.03155726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596901,"about_ca_system_score_gemma":0.003844503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001540134,"about_ca_topic_score_gemma":0.003480942,"domain_scores_codex":[0.9949195,0.002288746,0.0003095757,0.0007361276,0.001217691,0.0005283621],"domain_scores_gemma":[0.9955675,0.0009644277,0.000478152,0.0009173052,0.0008663578,0.001206233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006755407,0.00009113189,0.001633707,0.0002544776,0.00001520959,0.0002713008,0.006716245,0.0002725726,0.00129156,0.7210529,0.1854292,0.08290427],"study_design_scores_gemma":[0.000004233054,0.00004124053,0.0006878701,0.0001058116,0.000004086252,0.0002737319,0.001567133,0.00009441204,0.0002125523,0.02567019,0.9713249,0.00001378524],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01383284,0.004546904,0.03585568,0.04355024,0.004906653,0.0002244086,0.0003380267,0.001440866,0.8953044],"genre_scores_gemma":[0.138765,0.00646018,0.02297468,0.03336764,0.003200953,0.0003224714,0.0005354803,0.001462289,0.7929114],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05184036,"threshold_uncertainty_score":0.1734233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007225826586439655,"score_gpt":0.1828652250076359,"score_spread":0.1756393984211962,"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."}}