{"id":"W1516312676","doi":"","title":"Highly Cited Canada Articles in Science Citation Index Expanded: A Bibliometric Analysis","year":2015,"lang":"en","type":"article","venue":"Canadian social science","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Science Citation Index; Library science; Index (typography); Web of science; Bibliometrics; Citation analysis; Institution; Multidisciplinary approach; Political science; Social science; Sociology; Computer science; MEDLINE; World Wide Web; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003120513,0.0005947868,0.001398022,0.06364357,0.00244367,0.004998619,0.0009304513,0.0004071489,0.003980415],"category_scores_gemma":[0.02046128,0.000195659,0.001031236,0.1578791,0.0007485125,0.001225811,0.001849247,0.0004530514,0.0007919166],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02007123,"about_ca_system_score_gemma":0.03565793,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8359957,"about_ca_topic_score_gemma":0.8386743,"domain_scores_codex":[0.9920315,0.0003068289,0.0004684871,0.000444495,0.006148095,0.0006006536],"domain_scores_gemma":[0.9825907,0.002429119,0.002167924,0.0003712922,0.01150697,0.0009339106],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003514409,0.0001117524,0.7816629,0.002392238,0.001274973,0.000575055,0.004784508,0.002953255,0.001451941,0.006791593,0.03600977,0.1616405],"study_design_scores_gemma":[0.00002230118,0.00003752997,0.9488201,0.0001974638,0.0004327551,0.0002177526,0.002454293,0.004214898,0.0007456409,0.0007304313,0.04205883,0.00006812281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.790629,0.01251926,0.003702013,0.00122726,0.0001566889,0.0006340585,0.1223711,0.0005228135,0.06823786],"genre_scores_gemma":[0.9401237,0.007177706,0.005258834,0.0001211598,0.0001408204,0.0003529209,0.03765024,0.0001137406,0.009060889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9968795,"threshold_uncertainty_score":0.3299402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.400457680858481,"score_gpt":0.5049024716013509,"score_spread":0.1044447907428699,"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."}}