{"id":"W4290779485","doi":"10.1371/journal.pone.0272730","title":"National differences in dissemination and use of open access literature","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Dalhousie University; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Publishing; Publication; Scholarship; Political science; Bibliometrics; Information Dissemination; Library science; Business; Economic growth; Economics; World Wide Web; Advertising; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics","open_science"],"consensus_categories":[],"category_scores_codex":[0.00747385,0.0001306854,0.0005131165,0.006344378,0.0007942882,0.003610214,0.0006909444,0.0003749214,0.007183578],"category_scores_gemma":[0.04348527,0.0001888623,0.0004788604,0.01261018,0.0009717002,0.002752325,0.002422054,0.0005255756,0.001223107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128852,"about_ca_system_score_gemma":0.001543205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004888949,"about_ca_topic_score_gemma":0.007588846,"domain_scores_codex":[0.9916983,0.002198033,0.001534156,0.001042706,0.00252178,0.001005129],"domain_scores_gemma":[0.9462964,0.02437247,0.01200348,0.005156137,0.009113513,0.003058061],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002645087,0.0001398238,0.7714826,0.001892737,0.0004285018,0.0005516955,0.02995157,0.0003842784,0.001927304,0.01559995,0.008001923,0.169375],"study_design_scores_gemma":[0.000009692288,0.00005221081,0.94591,0.0006336723,0.00007696076,0.0005444861,0.01312081,0.0001885056,0.0007614583,0.001659702,0.03700167,0.00004087597],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9219653,0.008274678,0.001248953,0.002792446,0.0001544182,0.0000656273,0.003866541,0.00007655023,0.0615555],"genre_scores_gemma":[0.9916574,0.003106492,0.0009070464,0.0002395591,0.00004068045,0.00005389747,0.001645833,0.00003633028,0.002312837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9993091,"threshold_uncertainty_score":0.03952599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8288413072428364,"score_gpt":0.6094753142032667,"score_spread":0.2193659930395697,"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."}}