{"id":"W1548026587","doi":"10.1002/asi.23601","title":"Estimating open access mandate effectiveness: The <scp>MELIBEA</scp> score","year":2015,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal; University of Ottawa","funders":"","keywords":"Mandate; Predictive power; Directory; Actuarial science; Statistics; Predictive value; Medicine; Business; Operations management; Computer science; Mathematics; Economics; Political science; Internal medicine; Law; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02927331,0.0005939431,0.0009855757,0.01289375,0.0008010642,0.003193752,0.001564766,0.0008334047,0.006643913],"category_scores_gemma":[0.1206602,0.0003901677,0.002033234,0.01154429,0.001410374,0.003644615,0.004239131,0.001512164,0.002048018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00213659,"about_ca_system_score_gemma":0.003834191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008030486,"about_ca_topic_score_gemma":0.01075865,"domain_scores_codex":[0.9814449,0.005426865,0.003147077,0.001105129,0.007762305,0.001113617],"domain_scores_gemma":[0.850017,0.05722404,0.0536829,0.01115254,0.02020798,0.007715558],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000132909,0.0001415667,0.9688898,0.0001125516,0.0003628517,0.00002886008,0.0002823705,0.0009526234,0.0001785575,0.001513178,0.004340486,0.02306421],"study_design_scores_gemma":[0.00002444526,0.0002187214,0.9890124,0.00005461214,0.0001151496,0.00005538615,0.0003757898,0.004043397,0.0007487313,0.0009915228,0.004316595,0.00004323222],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547306,0.0004127007,0.009593807,0.001293091,0.00007927427,0.0004188601,0.0111465,0.0005001509,0.02182497],"genre_scores_gemma":[0.9819456,0.0001588453,0.008542578,0.000163908,0.0001011439,0.0006394051,0.006457069,0.0001271808,0.001864232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9984353,"threshold_uncertainty_score":0.1548139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.424618148705003,"score_gpt":0.5635768202144353,"score_spread":0.1389586715094323,"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."}}