{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","scholarly_communication"],"consensus_categories":["metaresearch","bibliometrics"],"category_scores_codex":[0.04286531,0.0001722507,0.0003724155,0.8138773,0.001205565,0.005289014,0.005154308,0.00009476436,0.0001186548],"category_scores_gemma":[0.06894001,0.0001474797,0.00008727541,0.9800926,0.002038422,0.002328826,0.0004307535,0.0002764648,0.00005862127],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.005950873,"about_ca_system_score_gemma":0.03095186,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9391933,"about_ca_topic_score_gemma":0.9797428,"domain_scores_codex":[0.9761279,0.0001649491,0.000715839,0.001211225,0.01989802,0.00188204],"domain_scores_gemma":[0.986482,0.0008914556,0.0002370404,0.0006218688,0.00813454,0.003633153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004637906,0.00002114353,0.9184352,7.215703e-7,0.000006097346,0.00004572871,0.0006181881,0.0001021005,0.0002869778,0.0009608344,0.002547599,0.07697078],"study_design_scores_gemma":[0.0002909155,0.00002890092,0.9761351,0.000002058485,0.00000784815,0.000001405821,0.004569602,0.01248159,0.0002782971,0.00177828,0.004193523,0.0002325268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663247,0.0002259839,0.0004109594,0.001290406,0.0005682206,0.0001919362,0.00004392327,0.00001471906,0.03092918],"genre_scores_gemma":[0.9989911,0.00001143874,0.0001247779,0.0004967713,0.00006211941,0.0000107166,0.000002229923,0.000006033837,0.0002948159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1662152,"threshold_uncertainty_score":0.9978651,"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."}}