{"id":"W2924656839","doi":"10.1016/j.heliyon.2019.e01243","title":"Corrigendum to “Citation analysis of scientific categories” [Heliyon 3 (5) (May 2017) e00300]","year":2019,"lang":"en","type":"erratum","venue":"Heliyon","topic":"Legal, Health, Environmental and COVID-19 Challenges","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Citation; Mistake; Compromise; Bibliometrics; Computer science; Scientific literature; Citation analysis; Information retrieval; Library science; Social science; Sociology; Political science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000523548,0.0005622049,0.001553356,0.001955037,0.000219168,0.00006873886,0.0003778271,0.0008374849,0.002017485],"category_scores_gemma":[0.0001920142,0.0005050942,0.0005548798,0.002067404,0.0002183797,0.0001388861,0.0001562212,0.0009462707,0.002299169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006762146,"about_ca_system_score_gemma":0.00112354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000224679,"about_ca_topic_score_gemma":0.0009942779,"domain_scores_codex":[0.9955298,0.0001307463,0.0009275877,0.001247929,0.001481007,0.0006828727],"domain_scores_gemma":[0.9970111,0.00006639931,0.0005829142,0.001504993,0.0002676964,0.000566932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004785534,0.0007967691,0.003477165,0.01761084,0.002198966,0.00008150186,0.004590218,0.00009176229,0.004744017,0.0003837986,0.962171,0.003375459],"study_design_scores_gemma":[0.0007299696,0.0007696187,0.02888316,0.001494603,0.00328977,0.000007350129,0.0007575022,0.0001318787,0.0006638378,0.00003171359,0.9626715,0.0005691614],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1403176,0.1601263,0.0008599039,0.02801115,0.3195677,0.01089405,0.003925288,0.0007469375,0.3355511],"genre_scores_gemma":[0.03995422,0.01766516,0.0002208094,0.002491297,0.001338243,0.0001103808,0.006421134,0.0001358524,0.9316629],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5961118,"threshold_uncertainty_score":0.9997401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04656131611740794,"score_gpt":0.3107281954773308,"score_spread":0.2641668793599228,"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."}}