{"id":"W2612497353","doi":"10.1111/conl.12359","title":"Unsupported Conclusions on Net Conservation Benefits of Mislabeling Seafood","year":2017,"lang":"en","type":"article","venue":"Conservation Letters","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"IUCN Red List; Ranking (information retrieval); Conservation status; Vagueness; Fishery; Biology; Geography; Statistics; Ecology; Computer science; Mathematics; Information retrieval; Artificial intelligence","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":[0.1873964,0.003082215,0.002956838,0.005691808,0.001700646,0.00648125,0.007213015,0.00545708,0.01359562],"category_scores_gemma":[0.4562825,0.001406409,0.01000911,0.005035511,0.009028301,0.0125303,0.005929436,0.009437235,0.003313856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002546324,"about_ca_system_score_gemma":0.003745321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00448838,"about_ca_topic_score_gemma":0.003970402,"domain_scores_codex":[0.8656554,0.08331271,0.01485346,0.01601325,0.01817024,0.001995027],"domain_scores_gemma":[0.46286,0.4574903,0.02333573,0.03471474,0.01965096,0.001948294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008422926,0.0005430973,0.08661792,0.07458399,0.1048971,0.001578552,0.006114672,0.01111735,0.005394155,0.2058938,0.1441417,0.3506947],"study_design_scores_gemma":[0.001764822,0.001006439,0.05144947,0.03561836,0.04803701,0.0008857817,0.004417799,0.008152274,0.008291523,0.6562226,0.1836778,0.0004761137],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.06842195,0.1905521,0.2557356,0.3381927,0.02907358,0.004025129,0.02471598,0.001883054,0.08739995],"genre_scores_gemma":[0.6945589,0.02196462,0.1054151,0.1546595,0.005342448,0.004159711,0.006197318,0.001039576,0.006662838],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1873964,"threshold_uncertainty_score":0.9910589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04282669357567789,"score_gpt":0.2887625676340864,"score_spread":0.2459358740584085,"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."}}