{"id":"W2483616777","doi":"10.15200/winn.147220.00404","title":"Knowledge Monopolies and Global Academic Publishing","year":2016,"lang":"en","type":"dataset","venue":"The Winnower","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intellectual property; Publishing; Private equity; Equity (law); Context (archaeology); Cash; Political science; Business; Library science; Management; Economics; Finance; Law; Computer science; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["bibliometrics","insufficient_payload"],"category_scores_codex":[0.02677274,0.0003013331,0.0004585738,0.02042934,0.0004378505,0.009322368,0.008573935,0.0006215827,0.00118056],"category_scores_gemma":[0.07078314,0.0001331747,0.0001256356,0.09524647,0.0006686261,0.001543273,0.004780423,0.001116322,0.002358626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001883598,"about_ca_system_score_gemma":0.0004023126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001836072,"about_ca_topic_score_gemma":0.00006978765,"domain_scores_codex":[0.9901103,0.0004474556,0.0007816268,0.0009440131,0.006878653,0.0008378956],"domain_scores_gemma":[0.9882272,0.006670972,0.0004471916,0.001984908,0.002236599,0.0004331604],"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":[0.000009523197,0.00001745424,0.0007145065,0.000004741211,0.00001676354,0.000002779828,0.0000216272,8.489786e-8,0.00000221273,0.0004325945,0.9430844,0.05569333],"study_design_scores_gemma":[0.0001947707,0.00003012799,0.003352039,0.00002632688,0.00001204885,0.00001458222,0.00007184946,0.00001568139,0.00000416777,0.02176071,0.9743161,0.0002015968],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008268812,0.008605121,0.00004766229,0.006865604,0.002000448,0.0002470408,0.9736117,0.00002186198,0.007773714],"genre_scores_gemma":[0.01904364,0.02896251,0.0001418753,0.00521379,0.01005221,0.0001564365,0.858224,0.0001133195,0.07809226],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1153877,"threshold_uncertainty_score":0.9997325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5500932074787537,"score_gpt":0.5878841795718969,"score_spread":0.03779097209314319,"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."}}