{"id":"W4389782617","doi":"10.1002/ieam.4881","title":"Assessing the relevance of environmental exposure data sets","year":2023,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Relevance (law); Context (archaeology); Computer science; Environmental data; Set (abstract data type); Risk analysis (engineering); Hazard; Data mining; Medicine; Geography","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.241912,0.001376687,0.002260666,0.01822356,0.002464858,0.01026089,0.003880102,0.003792553,0.002735327],"category_scores_gemma":[0.5236153,0.0009682019,0.003762026,0.01065138,0.004839956,0.00632652,0.01055557,0.004018449,0.0007887261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005509572,"about_ca_system_score_gemma":0.007251075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002988937,"about_ca_topic_score_gemma":0.002412462,"domain_scores_codex":[0.5900189,0.2560154,0.03583099,0.01045729,0.1048582,0.002819145],"domain_scores_gemma":[0.3181278,0.5513099,0.02771464,0.0296532,0.07103611,0.002158411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004052895,0.001293422,0.2530036,0.02321761,0.005252199,0.002463464,0.01537227,0.08562928,0.00927112,0.06528606,0.01976624,0.5153919],"study_design_scores_gemma":[0.001023365,0.005294701,0.2538201,0.02551984,0.004344369,0.003475542,0.02543095,0.1241823,0.0381356,0.3146982,0.2026234,0.001451625],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4248796,0.01589547,0.4440863,0.01738476,0.001690365,0.01195472,0.01589734,0.001344647,0.06686669],"genre_scores_gemma":[0.8093595,0.001981813,0.1772402,0.001224166,0.0004604429,0.003137727,0.005404009,0.0002098776,0.0009822155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.241912,"threshold_uncertainty_score":0.9348575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02637484181856662,"score_gpt":0.3019375643476552,"score_spread":0.2755627225290886,"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."}}