{"id":"W2016149065","doi":"10.1097/00003246-200512002-00283","title":"A GEOGRAPHICALLY AND TEMPORALLY COMPREHENSIVE ANALYSIS OF SEPTIC SHOCK: IMPACT OF AGE, SEX AND SOCIOECONOMIC STATUS.","year":2005,"lang":"en","type":"article","venue":"Critical Care Medicine","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre","funders":"","keywords":"Medicine; Socioeconomic status; Septic shock; Shock (circulatory); Demography; Gerontology; Environmental health; Sepsis; Internal medicine; Sociology","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":[0.0007313114,0.0001892856,0.000217212,0.001573632,0.0005241091,0.0004508372,0.0004308174,0.0003406371,0.002329442],"category_scores_gemma":[0.00349971,0.0002189459,0.0005569166,0.003384977,0.0001261493,0.0006075847,0.001119613,0.0005754198,0.000269889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003081888,"about_ca_system_score_gemma":0.001002894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03685867,"about_ca_topic_score_gemma":0.06470086,"domain_scores_codex":[0.9995182,0.0002168943,0.00006338531,0.00007677315,0.00006436323,0.00006040165],"domain_scores_gemma":[0.9983042,0.0004255798,0.0005703704,0.000174592,0.0002375975,0.0002875794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001769096,0.00003560967,0.9939151,0.00003388582,0.0001741719,0.00018234,0.0001690635,0.0001426196,0.0001416552,0.000115546,0.0006750734,0.004237942],"study_design_scores_gemma":[0.000004608454,0.00005784733,0.9986492,0.00001018024,0.00004989882,0.000159239,0.000496543,0.0001891286,0.00002610454,0.0000414971,0.0003109446,0.000004829655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943687,0.0005737737,0.0003897187,0.0003210951,0.00001228841,0.0000200063,0.003682304,0.000006583374,0.0006254161],"genre_scores_gemma":[0.9964006,0.0003780157,0.0007029147,0.00002951025,0.00001130027,0.00002576393,0.002124652,0.000004105989,0.0003231624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03685867,"threshold_uncertainty_score":0.07328826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054660664919902,"score_gpt":0.4436798798819932,"score_spread":0.3382138133900029,"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."}}