{"id":"W4241006630","doi":"10.1503/cmaj.045262","title":"Open access in medical publishing: trends and countertrends","year":2005,"lang":"en","type":"editorial","venue":"Canadian Medical Association Journal","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; World Wide Web; Publishing; Data science; Open access publishing; Information retrieval; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","scholarly_communication","research_integrity"],"category_scores_codex":[0.07623337,0.0004632909,0.001329012,0.003461394,0.0005749081,0.07440665,0.02818885,0.007678503,0.03403894],"category_scores_gemma":[0.3742793,0.0003681087,0.0001922215,0.003215179,0.0001737451,0.01838001,0.002896591,0.01545767,0.0001421472],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003791322,"about_ca_system_score_gemma":0.03721778,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04548992,"about_ca_topic_score_gemma":0.5625244,"domain_scores_codex":[0.9657277,0.001662369,0.002907942,0.001146514,0.02713673,0.001418769],"domain_scores_gemma":[0.9766019,0.01013763,0.002309384,0.0005692178,0.002479427,0.007902429],"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":[0.000009606793,0.00001707001,0.01231646,0.000001921936,0.00003685424,0.0004440075,0.0001487839,8.265116e-7,3.366625e-9,0.00003976342,0.6699739,0.3170108],"study_design_scores_gemma":[0.00172648,0.0000214826,0.008562405,0.000294514,0.00001835331,0.0001438178,0.0002037161,0.0004510641,4.948261e-8,0.001270816,0.9869027,0.0004046053],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0003781341,0.0007930895,0.00001522144,0.2990817,0.623463,0.0001080203,0.0004069824,0.00001992105,0.07573389],"genre_scores_gemma":[0.004222435,0.001251305,0.00002825371,0.01947496,0.9471621,0.00002151766,0.0002425722,0.00005820523,0.02753869],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.5170345,"threshold_uncertainty_score":0.9998771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05261810948990192,"score_gpt":0.4299659328664203,"score_spread":0.3773478233765183,"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."}}