{"id":"W7084086253","doi":"10.6084/m9.figshare.c.8059142.v1","title":"Non-coding RNAs as diagnostic biomarkers for preeclampsia: a systematic review and meta-analysis","year":2025,"lang":"en","type":"other","venue":"Figshare","topic":"X-ray Spectroscopy and Fluorescence Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diagnostic accuracy; Meta-analysis; Diagnostic odds ratio; Diagnostic test; Confidence interval; Odds ratio; microRNA; Systematic review","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000108489,0.0004587512,0.002879807,0.0003658166,0.00009727553,0.0001175901,0.0003546611,0.0001310144,0.3530264],"category_scores_gemma":[0.0004425849,0.0003534083,0.00206982,0.0007133581,0.00001039697,0.00005461507,0.000096203,0.0001462425,0.0005294018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000195608,"about_ca_system_score_gemma":0.00008542326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001794775,"about_ca_topic_score_gemma":0.0000370644,"domain_scores_codex":[0.9984067,0.00006225913,0.00045645,0.0005891172,0.0001891489,0.000296296],"domain_scores_gemma":[0.9980886,0.0004999891,0.0005483004,0.0006732282,0.00009363425,0.00009623305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"meta_analysis","study_design_scores_codex":[8.123235e-7,0.00002220399,0.000006620456,0.1445241,0.2128975,0.000002063005,0.000009303408,6.58676e-7,3.216018e-7,0.000142948,0.6423846,0.000008942792],"study_design_scores_gemma":[0.0001186729,0.00001943594,0.000004310373,0.03774214,0.9413205,2.720578e-7,0.0000338238,0.0001018722,0.00003039067,0.0001202223,0.02003842,0.0004699028],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[3.862213e-8,0.1745418,0.001817774,0.0003533196,0.00003406086,0.007161841,0.5698401,0.0001265358,0.2461245],"genre_scores_gemma":[0.0009445041,0.0007042452,0.0005473209,0.0008280119,0.0002729891,0.01451055,0.1791933,0.0003694159,0.8026297],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7284231,"threshold_uncertainty_score":0.9998918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388066490843802,"score_gpt":0.2968706452272722,"score_spread":0.2729899803188341,"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."}}