{"id":"W4221092010","doi":"10.2196/29967","title":"Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Ovarian function and disorders","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Polycystic ovary; Machine learning; Predictive modelling; Artificial intelligence; Observational study; Computer science; Feature (linguistics); Data set; Medicine; Data mining; Internal medicine; Obesity","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003698656,0.0004207465,0.0005339928,0.0007973147,0.0004294688,0.000667734,0.000730226,0.0006488582,0.001831189],"category_scores_gemma":[0.01527849,0.0003252401,0.001087395,0.0009984623,0.0002860201,0.0006222373,0.0006100914,0.001535463,0.0003722101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000453324,"about_ca_system_score_gemma":0.000854079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009213234,"about_ca_topic_score_gemma":0.006759477,"domain_scores_codex":[0.9985501,0.000800114,0.0001358353,0.000208349,0.0001894405,0.000116138],"domain_scores_gemma":[0.9849443,0.01013536,0.00209878,0.001353356,0.0009188037,0.0005494082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001398521,0.0004613929,0.9955244,0.00001968464,0.0001284654,0.0001083233,0.0001057019,0.0008865825,0.00003647661,0.00007162215,0.0003767461,0.002140673],"study_design_scores_gemma":[0.00006579583,0.0009674142,0.9403004,0.00003888012,0.0002170179,0.0007023384,0.0008614496,0.05544375,0.0001398202,0.0003977036,0.0008364939,0.00002890179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981147,0.00010183,0.0008604396,0.00008300957,0.000008218392,0.00002317955,0.0006646882,0.00001168854,0.0001321594],"genre_scores_gemma":[0.997691,0.00007183473,0.0007436235,0.00002322555,0.00001496804,0.00003207159,0.001295628,0.00000404128,0.0001235464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009213234,"threshold_uncertainty_score":0.01956064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1204105317859002,"score_gpt":0.3949745097744957,"score_spread":0.2745639779885954,"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."}}