{"id":"W4256048527","doi":"10.1101/2021.08.18.21262256","title":"Identification and Mitigation of High-Risk Pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Society for International Health","funders":"Global Affairs Canada; Grand Challenges Canada","keywords":"Medicine; Pregnancy; Population; Framingham Risk Score; Cohort; Risk assessment; Cohort study; Demography; Environmental health; Obstetrics; Disease; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006854976,0.0003151636,0.0002393653,0.0006610357,0.0005568611,0.0006932866,0.0002576468,0.0002989361,0.001136051],"category_scores_gemma":[0.001982613,0.0002350237,0.0002069329,0.0005200147,0.0002399116,0.0004243279,0.0008811048,0.0005248172,0.0001575289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004793413,"about_ca_system_score_gemma":0.001568642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01967531,"about_ca_topic_score_gemma":0.0302923,"domain_scores_codex":[0.9996079,0.0001786462,0.00004011908,0.00003322254,0.00004567303,0.00009448565],"domain_scores_gemma":[0.9994504,0.0001428305,0.0002020923,0.00001763591,0.00008160635,0.0001055121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008813915,0.0001199843,0.9717757,0.0001888743,0.000020186,0.0004506035,0.001822203,0.0001302519,0.0004327485,0.0001599883,0.000500873,0.02431027],"study_design_scores_gemma":[0.0000183446,0.0003547777,0.9763402,0.001240134,0.00005189869,0.001074699,0.0150183,0.001164493,0.0005089265,0.0003960876,0.003808248,0.00002382265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952342,0.001238148,0.0003670013,0.0006721966,0.00004073303,0.00008234657,0.0003582014,0.00000661283,0.002000503],"genre_scores_gemma":[0.9965197,0.0015536,0.001032359,0.0001095098,0.00001165379,0.00009445552,0.000174363,0.00000194655,0.0005025478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01967531,"threshold_uncertainty_score":0.03912157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01116452434025577,"score_gpt":0.2620841286887519,"score_spread":0.2509196043484961,"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."}}