{"id":"W2034537308","doi":"10.1111/j.1471-1842.2003.00456.x","title":"Evaluating digital libraries in the health sector. Part 1: measuring inputs and outputs","year":2003,"lang":"en","type":"article","venue":"Health Information & Libraries Journal","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Victoria University of Wellington; University of Victoria","keywords":"Mainstream; Relevance (law); Health sector; Digital library; Computer science; Digital health; Data science; Knowledge management; Health services; Health care; Political science; Medicine; Environmental health","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.07229614,0.001316018,0.001111109,0.009621068,0.002467515,0.009982213,0.001043382,0.001771679,0.005630901],"category_scores_gemma":[0.1433907,0.0005422653,0.001025507,0.01171489,0.003420884,0.00737543,0.005505928,0.0009851936,0.0009885611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006879577,"about_ca_system_score_gemma":0.008459763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002215811,"about_ca_topic_score_gemma":0.003185085,"domain_scores_codex":[0.8573457,0.112163,0.007404619,0.001639515,0.01950324,0.001943937],"domain_scores_gemma":[0.7396883,0.1975621,0.0214083,0.006455041,0.03148337,0.00340282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001728106,0.002462037,0.2793381,0.009618251,0.0004696026,0.0002196777,0.02299996,0.00908476,0.004794101,0.01871086,0.00484457,0.64573],"study_design_scores_gemma":[0.000703055,0.0214553,0.5245609,0.007421419,0.001413201,0.0007771289,0.1995372,0.02633843,0.08968397,0.05926519,0.06813922,0.0007050767],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8005443,0.007918347,0.0532878,0.004668582,0.0002455772,0.01181195,0.00260097,0.0003579961,0.1185646],"genre_scores_gemma":[0.9283079,0.002736966,0.05560341,0.0005502237,0.00009552012,0.005707121,0.0007333923,0.00007933061,0.006186078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9900178,"threshold_uncertainty_score":0.3823431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1896224854068019,"score_gpt":0.4148950807738426,"score_spread":0.2252725953670407,"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."}}