{"id":"W4404845569","doi":"10.1101/2024.11.28.24318140","title":"Urinary prostaglandin metabolites as biomarkers for human labour: Insights into future predictors","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Workplace Health and Well-being","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Urinary system; Prostaglandin; Medicine; Chemistry; Endocrinology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003091972,0.0007279439,0.0009311279,0.0009007251,0.0001839487,0.001174106,0.0004470181,0.0006846694,0.001843523],"category_scores_gemma":[0.006237658,0.0002587805,0.0003439627,0.001344205,0.0004907926,0.0007344501,0.0004384867,0.0008629046,0.0003104894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002238031,"about_ca_system_score_gemma":0.0005118633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009563964,"about_ca_topic_score_gemma":0.0008489969,"domain_scores_codex":[0.9991995,0.0004624169,0.00006460785,0.0001178941,0.00009686086,0.00005884171],"domain_scores_gemma":[0.9964848,0.001750297,0.0007920727,0.000320037,0.0003372491,0.0003155799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006819338,0.00007788369,0.9645959,0.0001404714,0.0002153849,0.0001682938,0.00006954735,0.0004822346,0.002417412,0.0004341496,0.0006629376,0.03005379],"study_design_scores_gemma":[0.00002778636,0.0006239638,0.9833271,0.0001407861,0.0002930614,0.0006808218,0.0002736605,0.007152569,0.001852762,0.002359478,0.00323358,0.00003440365],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9224491,0.05544394,0.01254742,0.004425743,0.000270003,0.00006104415,0.002303752,0.0001333718,0.002365717],"genre_scores_gemma":[0.9886414,0.005624254,0.003845898,0.0003065948,0.0002355016,0.00002824186,0.0006051823,0.0000140548,0.0006988411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003091972,"threshold_uncertainty_score":0.01635212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322873687000454,"score_gpt":0.3749890590955143,"score_spread":0.3517603222255097,"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."}}