{"id":"W4285019061","doi":"10.1177/08445621221112668","title":"Validating PreCHAT: A Digital Preconception Health Risk Assessment Tool to Improve Reproductive, Maternal and Child Health","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Nursing Research","topic":"Reproductive Health and Contraception","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; Public Health Agency of Canada; Public Health Ontario; University of Toronto; Guelph General Hospital","funders":"Ontario Ministry of Health and Long-Term Care","keywords":"Reproductive health; Risk assessment; Maternal health; Environmental health; Medicine; Risk analysis (engineering); Psychology; Computer science; Health services; Computer security; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006654684,0.000120084,0.0003586057,0.0007645561,0.001474922,0.0001869202,0.0001329251,0.00003267398,0.00008122304],"category_scores_gemma":[0.000854569,0.0001189924,0.00006268011,0.0004661398,0.0001263977,0.0003147324,0.00002904575,0.001543851,0.000003157613],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.005236798,"about_ca_system_score_gemma":0.005818831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003669693,"about_ca_topic_score_gemma":0.0002720015,"domain_scores_codex":[0.9966503,0.000656716,0.0006213957,0.0004701552,0.0007975899,0.0008038649],"domain_scores_gemma":[0.9971547,0.00005566138,0.0003988009,0.0003323149,0.0005671942,0.001491377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003830228,0.00009976311,0.03684538,0.0001009379,0.00002668168,0.00003120581,0.006050547,0.00008557634,0.0002015387,0.000107703,0.005653387,0.9504142],"study_design_scores_gemma":[0.002796393,0.01732669,0.9380881,0.002824671,0.00002827946,0.004624245,0.01377363,0.0003083548,0.0002469288,0.002925207,0.0167589,0.0002986411],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9216964,0.002143682,0.000482801,0.07282844,0.0007208297,0.001290315,0.00008870777,0.000009769163,0.0007390614],"genre_scores_gemma":[0.9965162,0.0001092007,0.001423398,0.0004259871,0.001171434,0.00003319058,0.00001077104,0.00002766765,0.0002821824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9501156,"threshold_uncertainty_score":0.999825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05907285014538263,"score_gpt":0.4276645893388509,"score_spread":0.3685917391934682,"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."}}