{"id":"W2996663025","doi":"10.18438/eblip29623","title":"Library Supported Open Access Funds: Criteria, Impact, and Viability","year":2019,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Business; Demographics; Impact factor; Index (typography); Accounting; Library science; Computer science; Finance; Public relations; Political science; World Wide Web; Sociology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.08071383,0.0004387677,0.0009943391,0.03659621,0.002492616,0.02108203,0.00197742,0.001267676,0.007367395],"category_scores_gemma":[0.3487997,0.0002620541,0.0007841001,0.04478385,0.004284917,0.01256894,0.01022044,0.0006964828,0.001183702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005397625,"about_ca_system_score_gemma":0.007629639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002142488,"about_ca_topic_score_gemma":0.002403521,"domain_scores_codex":[0.9047222,0.03613037,0.01290185,0.002444011,0.03971008,0.004091452],"domain_scores_gemma":[0.5158814,0.2793169,0.108301,0.01450064,0.06662861,0.0153714],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006404173,0.0002640374,0.7737469,0.001106459,0.0003627462,0.0003144461,0.005137261,0.0008291482,0.0003747264,0.02244729,0.005392277,0.1893843],"study_design_scores_gemma":[0.0001397482,0.0009858748,0.8707297,0.003393913,0.000561129,0.00130066,0.03377799,0.005514654,0.003089179,0.02819225,0.05207662,0.000238368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9222749,0.008348316,0.006050976,0.008097672,0.0002453765,0.0005704392,0.003026898,0.0001598414,0.05122552],"genre_scores_gemma":[0.994101,0.0008854031,0.002657058,0.0001431236,0.0002282342,0.000210002,0.0006269476,0.00002735908,0.00112087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9980226,"threshold_uncertainty_score":0.4268606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.368039928513771,"score_gpt":0.5709500403995352,"score_spread":0.2029101118857642,"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."}}