{"id":"W128588076","doi":"10.1023/a:1011850529748","title":"Resource Absorption in a Health Service System","year":2001,"lang":"en","type":"article","venue":"Health Care Management Science","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Health administration; Health informatics; Service (business); Resource distribution; Resource (disambiguation); Lorenz curve; Absorption (acoustics); Feature (linguistics); Computer science; Operations research; Resource allocation; Business; Medicine; Public health; Nursing; Mathematics; Marketing; Computer network; Materials science","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":[0.005537208,0.0001706674,0.0003075599,0.0006887521,0.00293454,0.00004872216,0.0004059879,0.00008129649,0.00005544032],"category_scores_gemma":[0.00005544752,0.0001673404,0.00002496959,0.003504817,0.00006196336,0.0003293874,0.0001853445,0.0004300688,0.0002730874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003810704,"about_ca_system_score_gemma":0.00155416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005218893,"about_ca_topic_score_gemma":0.004551213,"domain_scores_codex":[0.995473,0.000764769,0.00113346,0.000677263,0.0007224405,0.001229117],"domain_scores_gemma":[0.9981877,0.0000689246,0.000386609,0.0006068117,0.0003143889,0.0004355474],"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":[0.0003224543,0.0004043936,0.1042962,0.04459131,0.00002292968,0.0001075108,0.174932,0.07726525,0.00002332474,0.3635188,0.01920733,0.2153084],"study_design_scores_gemma":[0.002719807,0.0003808685,0.1421119,0.005872201,0.000006597993,0.00001427883,0.2987054,0.08224922,0.000001218889,0.00005901319,0.4672452,0.0006343394],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2964671,0.00401853,0.08414865,0.3474177,0.005260515,0.02201462,0.0000610459,0.002122265,0.2384896],"genre_scores_gemma":[0.9537874,0.000576945,0.01226051,0.03161556,0.000162165,0.0003846181,0.00007038296,0.00003040524,0.001111991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6573204,"threshold_uncertainty_score":0.9983635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0470054191491732,"score_gpt":0.4159584558989106,"score_spread":0.3689530367497373,"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."}}