{"id":"W2097082745","doi":"10.1109/picmet.1999.808098","title":"Knowledge network of contemporary interdisciplinary study of organization and technology: from bibliometrics to epistemology","year":2003,"lang":"en","type":"article","venue":"","topic":"University-Industry-Government Innovation Models","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bibliometrics; Context (archaeology); Field (mathematics); Knowledge management; Subject (documents); Domain (mathematical analysis); Sociology; Outcome (game theory); Engineering ethics; Epistemology; Management science; Computer science; Engineering; Mathematics; Philosophy","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"],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0002390378,0.00009891418,0.0002248646,0.0030537,0.00007392625,0.00002351856,0.0001690792,0.0001497398,0.0001451298],"category_scores_gemma":[0.0001840178,0.00009931922,0.000009498656,0.02323867,0.00004450442,0.0004029425,0.0006312966,0.0001104517,0.00001122696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000272142,"about_ca_system_score_gemma":0.00002409947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005781311,"about_ca_topic_score_gemma":0.00002444867,"domain_scores_codex":[0.9992377,0.00001540437,0.0003047772,0.0002032551,0.0001372616,0.0001015945],"domain_scores_gemma":[0.9989297,0.00005401816,0.000262213,0.0001954874,0.0005505305,0.000007992451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001722067,0.0004363595,0.9493232,0.00002971594,0.00005660238,0.000003532957,0.000138186,0.00007972441,0.0004590835,0.0405766,0.008467877,0.0004119493],"study_design_scores_gemma":[0.01631482,0.00172195,0.7569923,0.00047501,0.0006441697,0.00001118374,0.1005304,0.004713144,0.007942989,0.06553913,0.04273246,0.002382417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685039,0.00004094376,0.005187224,0.0003337144,0.0001448014,0.0003170505,0.000002186397,0.0000503664,0.02541984],"genre_scores_gemma":[0.9990058,9.676369e-7,0.0004388297,0.0001003772,0.00005551318,0.000001429634,0.00000969944,0.00001237767,0.0003750336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1923308,"threshold_uncertainty_score":0.9975229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03507373180136501,"score_gpt":0.260684868587617,"score_spread":0.225611136786252,"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."}}