{"id":"W2952984634","doi":"10.1002/asi.21062","title":"Comparing bibliometric statistics obtained from the Web of Science and Scopus","year":2009,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":791,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Scopus; Web of science; Comparability; Bibliometrics; Citation; Citation impact; Library science; Computer science; Impact factor; Database; Information retrieval; Data science; Statistics; Political science; Mathematics; MEDLINE","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","sts","scholarly_communication"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.02868934,0.00008756949,0.0003184153,0.08190859,0.0009967969,0.00132355,0.003648465,0.0000390633,0.000002188408],"category_scores_gemma":[0.05637012,0.00004240307,0.00009248457,0.6050199,0.01017726,0.002535862,0.0006570048,0.0002666993,0.000001301432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001343582,"about_ca_system_score_gemma":0.001608392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003199806,"about_ca_topic_score_gemma":0.000001532828,"domain_scores_codex":[0.9917624,0.00002568165,0.0008261605,0.0001799049,0.006832858,0.0003730092],"domain_scores_gemma":[0.9815208,0.00208919,0.001885225,0.0004446307,0.01390484,0.0001552558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000292866,0.00003707079,0.09949998,0.000004000544,0.00001673577,1.913723e-7,0.000744998,0.00002728794,0.01321349,0.009462762,0.01560942,0.8613548],"study_design_scores_gemma":[0.001072846,0.001123336,0.8545586,0.0000285583,0.00003204338,0.00005742517,0.01938832,0.05868367,0.006537169,0.03068239,0.02764563,0.0001899899],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843144,0.0002977994,0.006482378,0.008312645,0.0001949485,0.00017763,0.00003630698,0.000006619591,0.0001772254],"genre_scores_gemma":[0.9874241,0.0006381127,0.0110572,0.0008519037,0.00001877345,9.752248e-7,1.697071e-7,0.000001376908,0.000007349279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8611648,"threshold_uncertainty_score":0.9997132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2061078137298789,"score_gpt":0.4850023353701993,"score_spread":0.2788945216403204,"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."}}