{"id":"W4402405796","doi":"10.23889/ijpds.v9i5.2754","title":"The Kids’ Environment and Health Cohort: a novel administrative data resource for research on the environmental determinants of child health in England","year":2024,"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":"Resource (disambiguation); Child health; Health data; Environmental health; Environmental research; Environmental data; Medicine; Environmental resource management; Psychology; Computer science; Environmental science; Pediatrics; Political science; Health care; Economic growth; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01193767,0.000462025,0.001344901,0.004271452,0.001591146,0.003134721,0.001962933,0.001006485,0.009902962],"category_scores_gemma":[0.04632657,0.00128495,0.0008347176,0.005589917,0.0004683504,0.002264492,0.006825332,0.001476912,0.003913723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003577857,"about_ca_system_score_gemma":0.01462595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1806678,"about_ca_topic_score_gemma":0.2644034,"domain_scores_codex":[0.987956,0.003519763,0.003520281,0.001714831,0.0025918,0.0006972925],"domain_scores_gemma":[0.9556087,0.009752529,0.008090862,0.01039855,0.01090968,0.005239769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001114943,0.0003153741,0.6068963,0.0033626,0.0005273512,0.001594396,0.00874661,0.0008734369,0.001890285,0.005591401,0.2939606,0.07512663],"study_design_scores_gemma":[0.000598382,0.000224782,0.6589983,0.002374761,0.000216099,0.0008524121,0.00402268,0.001108097,0.0005128523,0.00117684,0.3297134,0.0002014514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1442643,0.003414756,0.01628325,0.004530669,0.0005733141,0.006332573,0.8146904,0.0005323231,0.009378637],"genre_scores_gemma":[0.2417288,0.005532309,0.07899955,0.002856613,0.0006448225,0.04193667,0.6139468,0.0006330474,0.01372148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1806678,"threshold_uncertainty_score":0.3592324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4262744920594909,"score_gpt":0.5245513289007545,"score_spread":0.09827683684126365,"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."}}