{"id":"W6931605367","doi":"10.5683/sp3/q4ulsx","title":"Impact of Adverse Childhood Experiences and Resilience on Adult Emergency Room","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Western University","funders":"","keywords":"Adverse Childhood Experiences; Resilience (materials science); Psychological resilience; Population; Emergency department; Health care; Adverse effect; Vulnerability (computing)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002170243,0.000234276,0.000254434,0.0002074285,0.0001808482,0.00002585656,0.001415316,0.00009294963,0.001192937],"category_scores_gemma":[0.0003514602,0.0001918848,0.000107709,0.0003410813,0.00004198588,0.0002310687,0.0003974185,0.0003278246,0.000003730251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004228198,"about_ca_system_score_gemma":0.000141709,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02929389,"about_ca_topic_score_gemma":0.0009724837,"domain_scores_codex":[0.9981458,0.0001693107,0.0003434009,0.0006207196,0.0005054807,0.0002152698],"domain_scores_gemma":[0.9979378,0.00006453118,0.0004058169,0.00141835,0.00006341007,0.0001100976],"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":[0.000009818756,0.0001178015,0.0003771428,0.00001923563,0.00001627526,0.000007584984,0.0008931802,0.00004756816,0.000001708331,0.0003429057,0.9951273,0.003039518],"study_design_scores_gemma":[0.0002478319,0.0009463194,0.1776901,0.00004524384,0.00002285729,0.00001718168,0.0003254379,0.0007037855,0.000005876055,0.0001237885,0.8194502,0.000421371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002092869,0.0001083714,0.0002026188,0.0000997618,0.0001807485,0.0001497081,0.996824,0.00004765721,0.0002942693],"genre_scores_gemma":[0.003912409,0.0005292983,0.0002241373,0.00004576811,0.00005498227,0.00007410259,0.9951241,0.000007755579,0.00002743554],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1773129,"threshold_uncertainty_score":0.9997201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009992132657145813,"score_gpt":0.2859608876552374,"score_spread":0.2759687549980916,"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."}}