{"id":"W2066170924","doi":"10.1016/s0840-4704(10)60411-5","title":"Prioritizing Resource Allocation for Clinical Enhancement: <i>A Participative Methodology</i>","year":2001,"lang":"en","type":"article","venue":"Healthcare Management Forum","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York Central Hospital","funders":"","keywords":"Prioritization; Task (project management); Resource allocation; Plan (archaeology); Process (computing); Process management; Order (exchange); Operations management; Strategic planning; Resource (disambiguation); Business; Computer science; Knowledge management; Management; Marketing; Geography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005513348,0.0002312978,0.0004562287,0.0001795254,0.002010486,0.00002507161,0.000214413,0.0003236644,0.0001008442],"category_scores_gemma":[0.0005201279,0.0002280529,0.0001268553,0.0004429662,0.00006076225,0.0001827641,0.0001451959,0.0005344794,0.0001463745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002807677,"about_ca_system_score_gemma":0.0002207131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002220699,"about_ca_topic_score_gemma":0.0006975574,"domain_scores_codex":[0.9940889,0.002248044,0.001586055,0.0006640789,0.000288027,0.001124922],"domain_scores_gemma":[0.9970093,0.001210143,0.0004370178,0.0005537069,0.0004937731,0.0002960611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001029934,0.0004605303,0.114167,0.00231395,0.0002598085,0.0000207008,0.005948829,0.0002068401,0.00003543726,0.4594007,0.0753811,0.3407751],"study_design_scores_gemma":[0.002188165,0.0005822292,0.007372895,0.0004233402,0.0000776384,0.000001715928,0.01546357,0.00786364,0.00001206026,0.003492033,0.9621665,0.000356238],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03369232,0.0008757423,0.7682719,0.1680862,0.002452046,0.009427342,0.00004024484,0.0004136189,0.01674055],"genre_scores_gemma":[0.6028479,0.00693104,0.297585,0.06326051,0.001525448,0.007351537,0.001010581,0.0001642422,0.01932369],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8867854,"threshold_uncertainty_score":0.9992887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3972222618067736,"score_gpt":0.5659615611925486,"score_spread":0.168739299385775,"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."}}