{"id":"W1799284535","doi":"10.1002/asi.23179","title":"Measuring academic influence: Not all citations are equal","year":2014,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":212,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université TÉLUQ; Université du Québec à Montréal; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Variety (cybernetics); Set (abstract data type); Selection (genetic algorithm); Feature (linguistics); Data set; Feature selection","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01342663,0.0006463145,0.001786508,0.01266601,0.001675184,0.004077801,0.001135257,0.00168801,0.002682258],"category_scores_gemma":[0.1864004,0.0003160251,0.0007938373,0.0227565,0.001964619,0.006734906,0.002116017,0.001090972,0.001025065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001487723,"about_ca_system_score_gemma":0.001434425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003035322,"about_ca_topic_score_gemma":0.003388514,"domain_scores_codex":[0.9806885,0.004793447,0.002516491,0.002004145,0.009417202,0.0005802019],"domain_scores_gemma":[0.8136631,0.1297294,0.02471947,0.01089472,0.0181987,0.00279454],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009118633,0.0003479875,0.5696468,0.001231338,0.001607262,0.0003242579,0.002581792,0.01128808,0.004427476,0.02758288,0.01050084,0.3695494],"study_design_scores_gemma":[0.0001768279,0.0008525921,0.7928025,0.0002970633,0.0009713317,0.001332603,0.001421129,0.0636891,0.009014348,0.0979549,0.03126346,0.0002241092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8368449,0.008571717,0.08421206,0.003030959,0.0005497974,0.0003619338,0.003021866,0.0009238139,0.06248299],"genre_scores_gemma":[0.9890144,0.0006141714,0.007856848,0.000152225,0.0004598469,0.0001002338,0.0006646352,0.00004622394,0.001091431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.987334,"threshold_uncertainty_score":0.07100767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3957544109113592,"score_gpt":0.5121693558521234,"score_spread":0.1164149449407643,"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."}}