{"id":"W2963703009","doi":"10.1002/asi.24184","title":"Does the web of science accurately represent chinese scientific performance?","year":2019,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"China; Web of science; Bibliometrics; Chinese science; Chinese academy of sciences; Publication; Computer science; Database; Library science; Political science; 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","scholarly_communication"],"consensus_categories":["metaresearch","bibliometrics"],"category_scores_codex":[0.07536337,0.0000766161,0.0002171573,0.02833041,0.001240892,0.00227667,0.004860746,0.00008226994,0.00001508232],"category_scores_gemma":[0.103777,0.00002662923,0.00009134622,0.1566145,0.002385109,0.006628406,0.0009298992,0.0002594981,0.00002788117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003100042,"about_ca_system_score_gemma":0.002085359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002192573,"about_ca_topic_score_gemma":0.000002039251,"domain_scores_codex":[0.9882903,0.00004204101,0.001014274,0.0002008836,0.01006576,0.0003868159],"domain_scores_gemma":[0.971706,0.001377955,0.002584721,0.0006649248,0.02357626,0.00009018511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002182652,0.00002999976,0.9133173,0.000009340772,0.000009930665,4.163282e-8,0.000615737,0.0001294941,0.01553286,0.008273298,0.002491957,0.05956821],"study_design_scores_gemma":[0.001247576,0.0003828642,0.7311677,0.00003159448,0.00001474225,0.00003297282,0.004266837,0.03262039,0.04943755,0.02261091,0.1580139,0.0001729877],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859544,0.00003233647,0.00005649882,0.008863582,0.002518262,0.0003199418,0.0000103948,0.000005858205,0.00223873],"genre_scores_gemma":[0.9987962,0.00006062932,0.0001402781,0.0000726019,0.00002183534,0.000003343083,1.47882e-7,0.000001430573,0.0009034933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1821496,"threshold_uncertainty_score":0.9987591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1517506622029389,"score_gpt":0.4773788652178922,"score_spread":0.3256282030149534,"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."}}