{"id":"W2075464897","doi":"10.1007/s11192-012-0859-6","title":"Characterizing a scientific elite (B): publication and citation patterns of the most highly cited scientists in environmental science and ecology","year":2012,"lang":"en","type":"article","venue":"Scientometrics","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Citation; Publishing; Publication; Elite; Productivity; Citation analysis; Library science; Ecology; Political science; Sociology; Biology; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics","metaresearch"],"domain":"incentives","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics","metaresearch"],"domain":"evaluation","study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"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":[0.06896877,0.0001695564,0.0002728926,0.1482552,0.0009451085,0.004050986,0.002212479,0.0001046378,0.0000641103],"category_scores_gemma":[0.06760544,0.0001168383,0.00004837319,0.4536093,0.002651048,0.003223875,0.002137082,0.0002516458,0.00002869701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000433768,"about_ca_system_score_gemma":0.0003471444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005557412,"about_ca_topic_score_gemma":0.00002216032,"domain_scores_codex":[0.9837248,0.0002661919,0.0008648708,0.001073345,0.01297681,0.001093919],"domain_scores_gemma":[0.9935562,0.001803566,0.0005942655,0.0009216093,0.00244432,0.0006800312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000458263,0.0001471349,0.8878684,0.000007167814,0.00000163685,3.326316e-7,0.0008201284,0.000001193899,0.04148963,0.0006697598,0.0001076892,0.06888234],"study_design_scores_gemma":[0.0003440464,0.00003760991,0.9871478,0.00001071367,0.000003806649,0.00001018024,0.0003664066,0.002541281,0.004473042,0.0001965574,0.004734856,0.0001336748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956776,0.0006994798,0.0001346355,0.0007187071,0.001670091,0.0004526699,0.0001011623,0.00001010916,0.0005355787],"genre_scores_gemma":[0.9988313,0.0001383028,0.000342686,0.0001629851,0.00003054688,0.00001347827,0.000008483442,0.000008122991,0.0004640881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3053541,"threshold_uncertainty_score":0.9969829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2644749148570341,"score_gpt":0.4612345109392629,"score_spread":0.1967595960822288,"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."}}