{"id":"W4328048685","doi":"10.2196/44666","title":"Early Triage of Critically Ill Adult Patients With Mushroom Poisoning: Machine Learning Approach","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Silymarin and Mushroom Poisoning","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Triage; Medicine; Machine learning; Receiver operating characteristic; Mushroom poisoning; Cohort; Artificial intelligence; Gradient boosting; Emergency medicine; Poison control; Internal medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001667544,0.000795236,0.0009729544,0.002883178,0.0004962247,0.0008820376,0.0008480218,0.0009573072,0.0009688622],"category_scores_gemma":[0.003913481,0.0002326012,0.0008298774,0.0009775679,0.0002963942,0.0007633098,0.000692886,0.001196613,0.0004077317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000738323,"about_ca_system_score_gemma":0.001201465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002451037,"about_ca_topic_score_gemma":0.002612818,"domain_scores_codex":[0.9992493,0.0002903515,0.0000966529,0.0001565373,0.00011562,0.00009153269],"domain_scores_gemma":[0.9982577,0.0007638862,0.0003553971,0.00005964132,0.0003909701,0.0001725654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001232343,0.001469024,0.4452031,0.0004198913,0.0003814968,0.0007471389,0.0003054435,0.112336,0.005626166,0.0007462324,0.005954683,0.4255786],"study_design_scores_gemma":[0.00008178605,0.000608869,0.0484639,0.00011907,0.0001556908,0.0004554795,0.0002638651,0.9440507,0.002295131,0.002483794,0.0009799702,0.00004171769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6640025,0.003079285,0.3231464,0.003876764,0.0003040535,0.0006696932,0.0006827305,0.001154331,0.00308421],"genre_scores_gemma":[0.9317476,0.0006751461,0.06577755,0.0003647879,0.0001901082,0.0001647248,0.0005686729,0.000012823,0.0004985777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002883178,"threshold_uncertainty_score":0.008818924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04218603155495339,"score_gpt":0.3695565706262773,"score_spread":0.327370539071324,"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."}}