{"id":"W2337465909","doi":"10.1061/9780784412688.034","title":"Evidence-Based Analyses of Hospital Site Selection for the Aging Population in Dallas, Texas","year":2012,"lang":"en","type":"article","venue":"","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Geographic information system; Population; Plan (archaeology); Decision support system; Health care; Process (computing); Knowledge management; Site selection; Selection (genetic algorithm); Computer science; Population ageing; Process management; Business; Geography; Medicine; Data mining; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06037178,0.0007269287,0.000889181,0.005783665,0.0009703813,0.002053051,0.002159829,0.00120426,0.004555977],"category_scores_gemma":[0.1369568,0.0003016298,0.002227945,0.006019064,0.001113583,0.001492295,0.001481729,0.001420311,0.0001378083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007678014,"about_ca_system_score_gemma":0.007389211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04795827,"about_ca_topic_score_gemma":0.05425915,"domain_scores_codex":[0.9594446,0.03495372,0.001745472,0.0009474815,0.001901521,0.001007221],"domain_scores_gemma":[0.7028425,0.2535344,0.02801188,0.003542034,0.009757358,0.002311728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003170585,0.001391377,0.8750576,0.002693947,0.006056383,0.0008754552,0.00131166,0.04769271,0.0001238218,0.0100804,0.007026009,0.04451995],"study_design_scores_gemma":[0.001887665,0.005083275,0.8106676,0.003949529,0.01260469,0.0004826728,0.01458842,0.1229547,0.001054296,0.0148138,0.01168812,0.0002251661],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9666813,0.006186588,0.007073007,0.007372355,0.00009897158,0.001005757,0.005244371,0.00002985286,0.006307705],"genre_scores_gemma":[0.9936772,0.001114937,0.003379622,0.0002874088,0.00004987334,0.0002537041,0.001000203,0.000004326998,0.0002327669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06037178,"threshold_uncertainty_score":0.3192803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2356547002247678,"score_gpt":0.2927733930962601,"score_spread":0.05711869287149227,"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."}}