{"id":"W2171257228","doi":"10.22230/src.2013v4n2a86","title":"Availability and Accessibility of Research Outputs in NARS: A case study with IARI","year":2013,"lang":"en","type":"article","venue":"Scholarly and Research Communication","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Work (physics); New delhi; Open access journal; Political science; Library science; Public relations; Business; Engineering; Computer science; Medicine; Geography; MEDLINE","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","bibliometrics","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01261126,0.0002607375,0.0006119486,0.01057607,0.002601074,0.006085203,0.001954035,0.0008795287,0.004348481],"category_scores_gemma":[0.04693804,0.0003204073,0.0004292242,0.02806404,0.001699281,0.004792103,0.005080112,0.001085883,0.001317932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00393836,"about_ca_system_score_gemma":0.002622667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01447603,"about_ca_topic_score_gemma":0.01702844,"domain_scores_codex":[0.9877935,0.005191848,0.001722766,0.001156985,0.003009971,0.001125083],"domain_scores_gemma":[0.8957481,0.05902649,0.02081744,0.008079388,0.01169703,0.004631556],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005875853,0.0006021966,0.6978219,0.001271987,0.0001646429,0.01205181,0.1694997,0.001629616,0.003384848,0.007050887,0.004763497,0.1011714],"study_design_scores_gemma":[0.00002629193,0.0003267744,0.7033067,0.0006055081,0.00009324374,0.006516988,0.2297511,0.002700317,0.001724688,0.001819515,0.05300821,0.0001206477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750363,0.0008815958,0.0007621471,0.001270896,0.00001521844,0.00007363378,0.0009536496,0.00007948728,0.02092705],"genre_scores_gemma":[0.9947482,0.0009810757,0.001184059,0.0001004629,0.00002833199,0.00005888125,0.0007469769,0.00003993882,0.002112113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9939148,"threshold_uncertainty_score":0.06669551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7214859327264074,"score_gpt":0.6436624978410018,"score_spread":0.07782343488540555,"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."}}