{"id":"W4403980396","doi":"10.5860/crl.85.7.978","title":"Training Needs and Preferences for Librarians Supporting Systematic Reviews in the Sciences, Humanities, and Social Sciences","year":2024,"lang":"en","type":"article","venue":"College & Research Libraries","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Association of Research Libraries; Association of Research Libraries","keywords":"Digital humanities; Training (meteorology); Library science; Medical education; Computer science; Sociology; Data science; Psychology; Humanities; Knowledge management; Medicine; Art; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.09770752,0.00029789,0.0009229497,0.007039926,0.004376767,0.008655226,0.001783313,0.004050264,0.008902579],"category_scores_gemma":[0.3477758,0.001048258,0.001129969,0.006860519,0.001992741,0.009634762,0.006262669,0.003614873,0.002435382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00470873,"about_ca_system_score_gemma":0.02194804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009869981,"about_ca_topic_score_gemma":0.02716198,"domain_scores_codex":[0.9365682,0.03229972,0.01203768,0.001868938,0.01241401,0.004811527],"domain_scores_gemma":[0.521408,0.3070073,0.04548884,0.008062035,0.06886807,0.04916569],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001007879,0.0008654569,0.3320732,0.007944194,0.000386156,0.002187164,0.1737188,0.0003067406,0.002554762,0.002444359,0.05393906,0.4225722],"study_design_scores_gemma":[0.0004531342,0.001073211,0.3261261,0.01349053,0.0004696268,0.006904904,0.4889405,0.001730721,0.001119584,0.007505076,0.1517128,0.0004737994],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6686719,0.01760372,0.003521261,0.2712359,0.0009994485,0.0008282693,0.0008419074,0.0003367188,0.03596083],"genre_scores_gemma":[0.9108444,0.01965249,0.02223023,0.03849259,0.0006682277,0.0007487882,0.0008650338,0.0001777251,0.006320516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9022925,"threshold_uncertainty_score":0.5167329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7199280995610257,"score_gpt":0.5691793647336214,"score_spread":0.1507487348274043,"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."}}