{"id":"W6945646103","doi":"10.25384/sage.20288872","title":"sj-docx-1-cjn-10.1177_08445621221112668 - Supplemental material for Validating PreCHAT: A Digital Preconception Health Risk Assessment Tool to Improve Reproductive, Maternal and Child Health","year":2022,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; University of Toronto","funders":"","keywords":"Risk assessment; Digital health; Child health; Health assessment; Health risk assessment; Risk management tools; Maternal health","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002999469,0.001147849,0.0009693718,0.003862941,0.002051694,0.0042662,0.002643925,0.002347751,0.9346865],"category_scores_gemma":[0.0541441,0.001154479,0.0008774565,0.00410457,0.0007274023,0.004124016,0.003091752,0.002141986,0.7107945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002054236,"about_ca_system_score_gemma":0.003881857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0304353,"about_ca_topic_score_gemma":0.04674423,"domain_scores_codex":[0.9979383,0.0002787992,0.0003027829,0.0002277714,0.001029926,0.0002223945],"domain_scores_gemma":[0.9590411,0.01764666,0.001122813,0.001753076,0.01859965,0.001836665],"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":[0.00003514476,0.00003481012,0.0001884884,0.0002699348,0.000002207228,0.00001037017,0.00005141381,0.00002238381,0.00004558827,0.0001708816,0.9924763,0.006692496],"study_design_scores_gemma":[0.0005054515,0.0000723875,0.005911768,0.001616068,0.00001832375,0.00008984224,0.0009303847,0.0003249933,0.0007599291,0.002014867,0.9876693,0.00008662847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006037063,0.00009261272,0.001386794,0.001743503,0.001240093,0.001128411,0.918151,0.00593571,0.06971821],"genre_scores_gemma":[0.008202919,0.0004933286,0.01138932,0.003995505,0.0008275254,0.00646278,0.6971359,0.0123335,0.2591592],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9346865,"threshold_uncertainty_score":0.09316164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06162589617513259,"score_gpt":0.4527955350628945,"score_spread":0.3911696388877619,"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."}}