{"id":"W6931238214","doi":"10.5281/zenodo.15487120","title":"Data Standards Manual (D4.2)","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"European Commission; UK Research and Innovation","keywords":"General partnership; Digital health; Reuse; Health data; Health care; Data collection; Value (mathematics); Health professionals","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":[0.02385012,0.001621468,0.001501708,0.01173439,0.002084,0.00912028,0.004803054,0.005101926,0.09762753],"category_scores_gemma":[0.05954188,0.002017572,0.001653874,0.01395328,0.001798372,0.00677617,0.004360837,0.005431792,0.1585502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004078756,"about_ca_system_score_gemma":0.01176834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01324724,"about_ca_topic_score_gemma":0.006546694,"domain_scores_codex":[0.9797055,0.005467467,0.005580357,0.001381064,0.006791384,0.00107431],"domain_scores_gemma":[0.941311,0.02052591,0.002952676,0.01365607,0.02022548,0.001328836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003527217,0.0001726861,0.001064818,0.002382172,0.00004795603,0.0002419537,0.000772078,0.001360873,0.004036953,0.06557433,0.8174607,0.1065328],"study_design_scores_gemma":[0.00005752633,0.00002288443,0.0006480539,0.0007212434,0.00001380985,0.0001450325,0.0001174619,0.000275565,0.001152935,0.00803624,0.9887738,0.00003531847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.002291112,0.002236695,0.2139063,0.006372546,0.001957844,0.004583523,0.4763173,0.047998,0.2443366],"genre_scores_gemma":[0.009551183,0.00319337,0.1664401,0.004411678,0.0004758813,0.007874069,0.7095222,0.01153537,0.08699599],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09762753,"threshold_uncertainty_score":0.3265966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04363144481752546,"score_gpt":0.336453309359522,"score_spread":0.2928218645419965,"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."}}