{"id":"W7096291199","doi":"","title":"Research Note Environmental Contaminant Concentrations in Canada Goose (Branta canadensis) Muscle: Probabilistic Risk Assessment for Human Consumers","year":2013,"lang":"en","type":"article","venue":"","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Goose; Wildlife; Consumption (sociology); Risk assessment; Food contaminant; Probabilistic logic; Agriculture","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006625215,0.0004278767,0.0002025446,0.0006040509,0.0005364665,0.0008384379,0.0004963386,0.0003642019,0.001243396],"category_scores_gemma":[0.001206153,0.0002136642,0.0005865635,0.0005032876,0.0003264096,0.0002360293,0.0004496126,0.0002894309,0.0001256968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003794571,"about_ca_system_score_gemma":0.002549086,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6654856,"about_ca_topic_score_gemma":0.7156096,"domain_scores_codex":[0.9997079,0.00004873645,0.000008471242,0.0000708109,0.0001374494,0.0000267097],"domain_scores_gemma":[0.9995597,0.000192338,0.00006799329,0.00002128339,0.0001364366,0.00002215234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003365979,0.0001571277,0.6401182,0.0001161429,0.0004462312,0.0004716974,0.0003465404,0.3155747,0.01146104,0.001670036,0.001175246,0.02812649],"study_design_scores_gemma":[0.00003276512,0.0006463119,0.2936324,0.00005081245,0.0003403535,0.000653495,0.0008692687,0.6898161,0.006183886,0.003096048,0.0045783,0.0001003403],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757392,0.0006104771,0.01685525,0.0003273871,0.000005265783,0.0001098309,0.001380558,0.00008697774,0.00488502],"genre_scores_gemma":[0.9916888,0.0004001091,0.00493526,0.00006411022,0.000002446444,0.00002385722,0.0007187733,0.0000104203,0.002156131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3345144,"threshold_uncertainty_score":0.6729689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836955704726016,"score_gpt":0.313845670099225,"score_spread":0.2854761130519648,"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."}}