{"id":"W3128587524","doi":"","title":"DIOXIN: GENERATION, TOXICITY, IMPACT ON PUBLIC HEALTH, ABATEMENT","year":2021,"lang":"en","type":"article","venue":"AIJR Abstracts","topic":"Human Health and Disease","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Smarter Alloys (Canada)","funders":"","keywords":"Public health; Environmental health; Business; Environmental planning; Natural resource economics; Environmental science; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003385314,0.000156098,0.0002583234,0.00008659107,0.0001632887,0.00006123908,0.00005149548,0.00006673481,0.001544854],"category_scores_gemma":[0.0002555896,0.0001285057,0.0001200129,0.0001507478,0.00002054663,0.0001057442,0.00002094672,0.0002059924,0.0005869343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002950785,"about_ca_system_score_gemma":0.002001646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001029463,"about_ca_topic_score_gemma":0.00009171379,"domain_scores_codex":[0.9983061,0.00006307933,0.0004248632,0.0003021671,0.0003900026,0.0005137721],"domain_scores_gemma":[0.9979525,0.00004184437,0.0001085674,0.0004093439,0.0001730696,0.001314743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000479706,0.009109878,0.04192294,0.001454769,0.0004273077,0.002716029,0.002150238,0.0008071234,0.01345193,0.004192602,0.7947662,0.1285213],"study_design_scores_gemma":[0.002478095,0.001199764,0.92704,0.0001130543,0.00002940668,0.0001168089,0.0001208821,0.0001331027,0.009113288,0.0001647382,0.05922263,0.0002681742],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9538131,0.0007310801,0.00002325117,0.03408783,0.0002613522,0.0003164998,0.00002712771,0.00007473907,0.01066497],"genre_scores_gemma":[0.9666142,0.0001359833,0.0001184099,0.03105895,0.0007887299,0.00001939376,0.0003457576,0.00001998416,0.000898555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8851171,"threshold_uncertainty_score":0.9993679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.100614406929855,"score_gpt":0.3866288565892188,"score_spread":0.2860144496593637,"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."}}