{"id":"W4413401094","doi":"10.1080/01605682.2025.2546058","title":"Patient segmentation and resource allocation for tailored healthcare delivery","year":2025,"lang":"en","type":"article","venue":"Journal of the Operational Research Society","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Blood Services","keywords":"Health care; Computer science; Healthcare delivery; Purchasing; Resource allocation; Project management; Segmentation; Business; Operations management; Knowledge management; Operations research; Artificial intelligence; Marketing; Engineering; Systems engineering; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002805053,0.0007831006,0.001082601,0.001545837,0.0007777535,0.001346632,0.00122328,0.001138741,0.001712169],"category_scores_gemma":[0.009255473,0.0005314174,0.0007130506,0.001390802,0.0005663896,0.001400445,0.001239413,0.001216014,0.0002993111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001779986,"about_ca_system_score_gemma":0.00339179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008749597,"about_ca_topic_score_gemma":0.01175679,"domain_scores_codex":[0.9979621,0.0009695386,0.0001289091,0.0004217378,0.0003237303,0.0001939432],"domain_scores_gemma":[0.9967836,0.001925237,0.0003921334,0.000255601,0.0004297983,0.0002136018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002429891,0.0003554057,0.01143576,0.0001286422,0.000125306,0.0001431381,0.0006671615,0.7498422,0.003613362,0.01383588,0.004112406,0.2154977],"study_design_scores_gemma":[0.00002085106,0.00006495825,0.001366551,0.00001757606,0.00002078796,0.00004293138,0.0001451963,0.9839012,0.001627507,0.01142058,0.001353737,0.00001806806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04582976,0.0001519899,0.9502631,0.0007709182,0.00003193289,0.0003161215,0.0001990277,0.0005028376,0.001934242],"genre_scores_gemma":[0.5763357,0.0001263189,0.4217193,0.0002450584,0.000039375,0.0002565389,0.0004230094,0.00008423441,0.0007705969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008749597,"threshold_uncertainty_score":0.01739734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0265614889590065,"score_gpt":0.3436137566803511,"score_spread":0.3170522677213446,"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."}}