{"id":"W4384497338","doi":"","title":"Domestic and Foreign Experience in Forming of Documental Flow in Scientifi c Libraries Under the State Publishing Programs","year":2017,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Library Science and Information","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Publishing; State (computer science); Political science; Flow (mathematics); Library science; Business; Computer science; Mathematics; Programming language; Law; Geometry","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":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00195625,0.0001517104,0.0002935256,0.0005835461,0.000514143,0.02184502,0.00680907,0.00004158251,0.00009440875],"category_scores_gemma":[0.0002378219,0.0001060319,0.0000471496,0.0009975014,0.0005232213,0.127267,0.002878916,0.0002287854,0.00000105601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003748008,"about_ca_system_score_gemma":0.0001863833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007977317,"about_ca_topic_score_gemma":0.00007003625,"domain_scores_codex":[0.997898,0.00008875171,0.0006902675,0.0003029781,0.0006570467,0.0003629755],"domain_scores_gemma":[0.9982013,0.0001544699,0.0008175518,0.0006294934,0.00008331421,0.0001138666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004137595,0.0001203859,0.8105224,0.0000886783,0.00001399964,0.00001856105,0.01295604,0.0008930456,0.002798811,0.007990008,0.0005705127,0.1639861],"study_design_scores_gemma":[0.0005513917,0.00001604361,0.8514546,0.000576888,0.000002724979,0.00001658519,0.001683167,0.03284232,0.01208874,0.1002598,0.0002578926,0.000249897],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915219,0.0009250801,0.003670322,0.0003431926,0.0003317128,0.0004224664,0.000003125609,0.00001418712,0.002768032],"genre_scores_gemma":[0.9973473,0.0004181904,0.001970839,0.0001633824,0.00001632104,0.00002788027,0.000002153428,0.000005925832,0.00004803499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1637363,"threshold_uncertainty_score":0.9985645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2299842136744947,"score_gpt":0.4959586079969396,"score_spread":0.2659743943224449,"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."}}