{"id":"W4206527080","doi":"10.2196/32357","title":"Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case","year":2021,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Environmental Health Sciences; National Institutes of Health; U.S. Environmental Protection Agency","keywords":"Asthma; Medicine; Bonferroni correction; Residence; Cohort; Prednisone; Environmental health; Demography; Statistics; Internal medicine","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":[0.01158822,0.001323747,0.000759283,0.002730642,0.0007519742,0.002866639,0.002851505,0.0016151,0.007546709],"category_scores_gemma":[0.03807041,0.0009321833,0.001725356,0.001351598,0.0009144067,0.004020284,0.006886477,0.002063019,0.002054221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008438098,"about_ca_system_score_gemma":0.002025753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00323204,"about_ca_topic_score_gemma":0.003163529,"domain_scores_codex":[0.992765,0.002048945,0.001106371,0.001394276,0.002275581,0.000409821],"domain_scores_gemma":[0.9681737,0.02176432,0.001730207,0.004538924,0.002728777,0.00106412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003327468,0.00299218,0.1342963,0.003311255,0.0008509048,0.0127693,0.01802221,0.02892737,0.04587534,0.01745135,0.09769578,0.6344807],"study_design_scores_gemma":[0.001390232,0.001620888,0.1224892,0.001653192,0.0005894243,0.007649155,0.006047666,0.4398563,0.08076713,0.04132237,0.2957803,0.0008341056],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1657757,0.0003513991,0.651683,0.00286652,0.0003212107,0.003679793,0.01473864,0.1520606,0.008523107],"genre_scores_gemma":[0.3265516,0.0003438601,0.6270301,0.00111878,0.0001576684,0.003191915,0.02485964,0.00973967,0.007006666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01158822,"threshold_uncertainty_score":0.06128508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1657037319229738,"score_gpt":0.4614659450861402,"score_spread":0.2957622131631664,"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."}}