{"id":"W137662695","doi":"","title":"Exploring the Intellectual Core and Impact of the Knowledge Management and Intellectual Capital Academic Discipline","year":2012,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Intellectual Capital and Performance Analysis","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Lakehead University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Intellectual capital; Core Knowledge; Knowledge management; Discipline; Citation; Engineering ethics; Sociology; Computer science; Library science; Engineering; Social science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001758925,0.0001188173,0.0002067217,0.0002217185,0.0003589149,0.0001737651,0.0002838065,0.00005133535,0.000007835576],"category_scores_gemma":[0.0009041853,0.00005284204,0.0002267153,0.0004933479,0.00004358995,0.003055275,0.00022511,0.0002382923,0.00001868608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001774047,"about_ca_system_score_gemma":0.00001960091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002864967,"about_ca_topic_score_gemma":0.000004927301,"domain_scores_codex":[0.9987213,0.00002662979,0.0006675125,0.0000399234,0.0003587857,0.0001858338],"domain_scores_gemma":[0.9977099,0.0003958563,0.001324533,0.0001069555,0.0004478084,0.00001489002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00092927,0.0002207958,0.5077084,0.002381491,0.003975531,1.270074e-7,0.2813313,0.005086975,0.0002899532,0.05067042,0.1206563,0.02674949],"study_design_scores_gemma":[0.003285813,0.0002633356,0.5729011,0.001077444,0.002000815,0.00008456348,0.1240031,0.05365793,0.0003650773,0.0009122694,0.2406527,0.0007958866],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952883,0.000526478,0.0001479246,0.0001857932,0.001161263,0.0003373181,0.000007029806,0.000006047589,0.002339922],"genre_scores_gemma":[0.9984418,0.0002032805,0.000003101954,0.00007055506,0.0007436863,0.000014058,0.000003387947,0.00000643779,0.000513714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1573282,"threshold_uncertainty_score":0.2760519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05926296356951588,"score_gpt":0.2711109363440667,"score_spread":0.2118479727745508,"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."}}