{"id":"W2423366126","doi":"10.18438/b85p87","title":"E-Journal Metrics for Collection Management: Exploring Disciplinary Usage Differences in Scopus and Web of Science","year":2016,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scopus; Publication; Citation; Ranking (information retrieval); Discipline; Journal ranking; Proxy (statistics); Computer science; Download; Publishing; Impact factor; The Internet; Web of science; Citation impact; World Wide Web; Library science; Information retrieval; MEDLINE; Sociology; Social science; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.04940815,0.0006149485,0.0009816516,0.02113562,0.001092943,0.005786783,0.001463999,0.0007581652,0.001530033],"category_scores_gemma":[0.2128312,0.0003008509,0.001206056,0.03327938,0.0009848155,0.005312939,0.002818912,0.0008607358,0.0004148754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002189544,"about_ca_system_score_gemma":0.002402768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004712906,"about_ca_topic_score_gemma":0.006200772,"domain_scores_codex":[0.9527103,0.01952012,0.009057995,0.00271348,0.01492005,0.001077975],"domain_scores_gemma":[0.685718,0.1777844,0.08437415,0.0151024,0.03195017,0.005070762],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002750219,0.0002016602,0.9273944,0.000496156,0.000625132,0.00005850664,0.003210648,0.001145461,0.0007127075,0.001288109,0.001752089,0.06284018],"study_design_scores_gemma":[0.00001564196,0.0003786784,0.9859868,0.0001332303,0.00008006219,0.0001559567,0.003066498,0.005335291,0.0007378289,0.001049302,0.003009457,0.00005123228],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819806,0.00112492,0.007094697,0.0006283242,0.00004830636,0.000320903,0.003684839,0.0003142481,0.004803017],"genre_scores_gemma":[0.9849775,0.0002305988,0.01071815,0.00006027767,0.00004791824,0.0003710269,0.002916276,0.00008476116,0.0005936045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9788644,"threshold_uncertainty_score":0.2612984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4265154132052441,"score_gpt":0.4844035526276532,"score_spread":0.05788813942240906,"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."}}