{"id":"W4392191913","doi":"10.1002/ieam.4897","title":"Integrating emerging science to improve estimates of risk to wildlife from chemical exposure: What are the challenges?","year":2024,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Environment and Climate Change Canada","funders":"","keywords":"Wildlife; Environmental science; Environmental planning; Risk assessment; Environmental health; Environmental resource management; Environmental protection; Computer science; Ecology; Biology; Medicine","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":[0.0429241,0.002720539,0.002655722,0.005063578,0.001073773,0.009609601,0.004263813,0.005141047,0.004289088],"category_scores_gemma":[0.05095078,0.001032644,0.002720798,0.003965672,0.003367523,0.01598486,0.006763697,0.006980352,0.001301867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003686257,"about_ca_system_score_gemma":0.01001038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009706175,"about_ca_topic_score_gemma":0.01196856,"domain_scores_codex":[0.9875644,0.006240176,0.0008091251,0.001187436,0.003766151,0.0004326935],"domain_scores_gemma":[0.9457788,0.03155835,0.003020213,0.003197074,0.01538635,0.001059144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000123249,0.0006151352,0.01850522,0.005883641,0.0009025705,0.0002215017,0.0006389857,0.0420059,0.004270106,0.06164204,0.01787131,0.8473204],"study_design_scores_gemma":[0.0001275838,0.001218493,0.01595618,0.0091474,0.00105988,0.0004182225,0.005007042,0.1775649,0.01259539,0.5679526,0.2084871,0.0004653407],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01872835,0.1842491,0.6541787,0.1198839,0.00270808,0.0006515698,0.000997794,0.0006128186,0.01798969],"genre_scores_gemma":[0.1291917,0.161351,0.6939053,0.00912715,0.002087933,0.000599657,0.001008448,0.0002192393,0.002509522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0429241,"threshold_uncertainty_score":0.227007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008392845136160478,"score_gpt":0.2550389101919437,"score_spread":0.2466460650557833,"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."}}