{"id":"W2612430136","doi":"10.1016/j.heliyon.2017.e00300","title":"Citation analysis of scientific categories","year":2017,"lang":"en","type":"article","venue":"Heliyon","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Citation analysis; Citation; Bibliometrics; Data science; Management science; Computer science; Library science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008755297,0.0009978737,0.001944966,0.1614107,0.001895675,0.005941928,0.001675699,0.0008402506,0.01474351],"category_scores_gemma":[0.07225358,0.0002688619,0.001982145,0.1788997,0.0009069934,0.003022392,0.002680134,0.0006557829,0.004902411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002983691,"about_ca_system_score_gemma":0.00454183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008225814,"about_ca_topic_score_gemma":0.00495074,"domain_scores_codex":[0.9820588,0.003217982,0.003301268,0.001648874,0.00894288,0.0008301746],"domain_scores_gemma":[0.9313145,0.0292176,0.009204164,0.005134283,0.02366716,0.001462245],"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":[0.0005570116,0.0002171983,0.2015925,0.008596003,0.001648123,0.000300737,0.003719009,0.004612043,0.00235924,0.06014739,0.07866845,0.6375823],"study_design_scores_gemma":[0.000114361,0.0003665545,0.3787044,0.001877831,0.0009598892,0.001165879,0.004616877,0.01579691,0.004006882,0.06322268,0.5289017,0.0002659865],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3266373,0.04026714,0.05223356,0.001874784,0.001420322,0.003302679,0.3214602,0.005416342,0.2473878],"genre_scores_gemma":[0.7295282,0.01201129,0.06289637,0.000281148,0.0008647384,0.004087619,0.166181,0.0008872914,0.02326233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8385893,"threshold_uncertainty_score":0.04932195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6441124752737633,"score_gpt":0.5944176859984289,"score_spread":0.04969478927533433,"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."}}