{"id":"W2266204788","doi":"10.1017/s1049023x0002553x","title":"Theme 4. Effective Models for Medical and Health Response Coordination: Summary and Action Plan","year":2001,"lang":"en","type":"article","venue":"Prehospital and Disaster Medicine","topic":"Disaster Response and Management","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Armed Forces; Capital Regional District","funders":"","keywords":"Theme (computing); Action (physics); Mandate; Identification (biology); Strengths and weaknesses; Plan (archaeology); Public relations; Action plan; Set (abstract data type); Process management; Incentive; Emergency management; Computer science; Psychology; Political science; Business; Management; Social psychology; Law","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":[0.04813643,0.002049084,0.0008545317,0.002139693,0.003292307,0.008745666,0.005458361,0.007845493,0.01661419],"category_scores_gemma":[0.03854644,0.0007637831,0.001916458,0.001477313,0.003847513,0.01064387,0.0114376,0.008246812,0.004302649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01092732,"about_ca_system_score_gemma":0.04422847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003043024,"about_ca_topic_score_gemma":0.002937891,"domain_scores_codex":[0.975969,0.01423649,0.001449026,0.001259419,0.004970084,0.002115903],"domain_scores_gemma":[0.978555,0.007458111,0.001928052,0.001450127,0.007115073,0.003493633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002674276,0.0007344333,0.002188426,0.008964332,0.00009666219,0.0006569522,0.0387307,0.008976581,0.003061467,0.2180844,0.4157683,0.3024702],"study_design_scores_gemma":[0.00009897888,0.0006262749,0.002259605,0.00816224,0.00007036763,0.0006033474,0.03294825,0.005402811,0.002234103,0.09321082,0.8542464,0.00013673],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01827624,0.01079945,0.2443604,0.5486676,0.01488648,0.01610093,0.001448573,0.001312184,0.1441483],"genre_scores_gemma":[0.2682821,0.02311184,0.52586,0.04170866,0.005579881,0.0319374,0.003407283,0.0006042347,0.09950866],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04813643,"threshold_uncertainty_score":0.2545728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08460010183633869,"score_gpt":0.4227128773044943,"score_spread":0.3381127754681555,"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."}}