{"id":"W2794535208","doi":"10.11575/prism/29072","title":"Building institutional support: how we & others have done it ... good?","year":2004,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nova scotia; Presentation (obstetrics); Library science; Political science; World Wide Web; Computer science; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02475612,0.0009033994,0.0006006242,0.001837176,0.01408413,0.02903752,0.002529402,0.00608379,0.01930865],"category_scores_gemma":[0.02318322,0.0005681555,0.0005919159,0.003094928,0.01431257,0.02424661,0.008253449,0.008514619,0.008329738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01143784,"about_ca_system_score_gemma":0.02374306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07852207,"about_ca_topic_score_gemma":0.1219667,"domain_scores_codex":[0.9859685,0.00649948,0.0004457501,0.000857065,0.003512498,0.002716816],"domain_scores_gemma":[0.9786621,0.003674467,0.0007933306,0.003008889,0.007006749,0.006854508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004632636,0.0001171136,0.004152926,0.0008973079,0.00007215557,0.0003619672,0.03569047,0.0007319285,0.001028898,0.1344479,0.4616856,0.3607674],"study_design_scores_gemma":[0.00001099588,0.00004010887,0.001145371,0.0006719199,0.00002767888,0.0001329447,0.03515524,0.0002721427,0.0006411376,0.02268499,0.9391604,0.00005712365],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.007841831,0.01388855,0.02914207,0.8027604,0.005662792,0.0001308857,0.0001752226,0.001614482,0.1387837],"genre_scores_gemma":[0.4482354,0.04498519,0.08872392,0.1370665,0.003305105,0.0002711102,0.0007379151,0.002244833,0.27443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07852207,"threshold_uncertainty_score":0.1561301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02247909917186591,"score_gpt":0.2210122055361951,"score_spread":0.1985331063643292,"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."}}