{"id":"W4413775409","doi":"10.23889/ijpds.v10i4.3155","title":"The Kids’ Environment and Health Cohort: a novel administrative data resource for research on the environmental determinants of child health in England","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Child health; Resource (disambiguation); Health data; Environmental health; Environmental data; Business; Environmental resource management; Environmental planning; Medicine; Political science; Computer science; Geography; Environmental science; Economic growth; Pediatrics; Health care; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01105717,0.00008901913,0.00013019,0.0001279549,0.001386092,0.0001530328,0.002028344,0.00002358321,0.00002121164],"category_scores_gemma":[0.0006007192,0.00005642997,0.00001513858,0.0001711627,0.0005316084,0.0005340377,0.001079123,0.0002152169,0.000001897589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005866943,"about_ca_system_score_gemma":0.0001372634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004396094,"about_ca_topic_score_gemma":0.001803144,"domain_scores_codex":[0.9977478,0.00009742637,0.0005195037,0.0004338903,0.0008144369,0.0003868753],"domain_scores_gemma":[0.9981971,0.0006868897,0.0003409318,0.0006265889,0.00001433,0.0001341869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007745547,0.0006191018,0.6631916,0.00004053834,0.0000331079,0.000001930623,0.001991329,0.0005204308,0.0003012303,0.004754034,0.02987262,0.2978995],"study_design_scores_gemma":[0.0007521517,0.0003040205,0.8509249,0.0001991254,0.000002894955,0.00002294357,0.0005315177,0.02455122,0.00004489202,0.00110441,0.1214885,0.00007341534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7619342,0.0005469141,0.001693384,0.2241483,0.0008432029,0.003654566,0.006906716,0.000007292742,0.000265392],"genre_scores_gemma":[0.9956694,0.001198937,0.0006525819,0.001918192,0.00009007049,0.00002976579,0.0003560716,0.000006394469,0.00007862263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2978261,"threshold_uncertainty_score":0.999914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3811615550069739,"score_gpt":0.5228636901232881,"score_spread":0.1417021351163143,"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."}}