{"id":"W2331671813","doi":"10.1097/hp.0b013e3181c64f90","title":"MEDECOR—A MEDICAL DECORPORATION TOOL TO ASSIST FIRST RESPONDERS, RECEIVERS, AND MEDICAL REACH-BACK PERSONNEL IN TRIAGE, TREATMENT, AND RISK ASSESSMENT AFTER INTERNALIZATION OF RADIONUCLIDES","year":2010,"lang":"en","type":"article","venue":"Health Physics","topic":"Disaster Response and Management","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Triage; Internalization; Radionuclide; Risk assessment; Medicine; Medical physics; Medical emergency; Environmental health; Computer science; Computer security; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002007943,0.002242112,0.001373918,0.002341185,0.0004389529,0.001796271,0.002598203,0.001206937,0.0482911],"category_scores_gemma":[0.008529725,0.0009848652,0.0009309674,0.0008490058,0.0004124526,0.001591141,0.002065879,0.00103059,0.01484308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006087495,"about_ca_system_score_gemma":0.001308455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002249025,"about_ca_topic_score_gemma":0.002400333,"domain_scores_codex":[0.9990767,0.0002076967,0.0001113789,0.0001454979,0.0003981238,0.00006052763],"domain_scores_gemma":[0.9946291,0.00336866,0.0004685517,0.0004808273,0.0006805954,0.0003723339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001829291,0.000469461,0.006339788,0.00152753,0.000206008,0.0009174903,0.0005354395,0.006356418,0.01219414,0.003564794,0.3252526,0.640807],"study_design_scores_gemma":[0.001714002,0.0009740397,0.0209691,0.001599764,0.0002904647,0.00483758,0.0003758149,0.16852,0.04141901,0.01258641,0.746063,0.0006507267],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01660585,0.001897409,0.3600915,0.001639135,0.0004429496,0.001620301,0.01770119,0.5750041,0.02499759],"genre_scores_gemma":[0.1793326,0.003268533,0.6798858,0.003740796,0.0005459001,0.00239847,0.03236052,0.03749637,0.06097101],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0482911,"threshold_uncertainty_score":0.1615499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04149075235444922,"score_gpt":0.4235170015487176,"score_spread":0.3820262491942684,"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."}}