{"id":"W3088667018","doi":"10.1002/fsn3.1882","title":"Consumers' attention on identification, nutritional compounds, and safety in heavy metals of Canadian sea cucumber in Chinese food market","year":2020,"lang":"en","type":"article","venue":"Food Science & Nutrition","topic":"Echinoderm biology and ecology","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Heavy metals; Identification (biology); Food safety; Chinese market; Business; Food market; Natural resource economics; Agricultural economics; Environmental science; Food science; Chemistry; Biology; China; Geography; Environmental chemistry; Agriculture; Economics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005803199,0.00009452085,0.0001741439,0.0001601977,0.0001957247,0.00002834299,0.0001785584,0.0001013776,0.0001041401],"category_scores_gemma":[0.0001386814,0.0000525979,0.00003100232,0.00154078,0.0003292268,0.0002572966,0.00002993955,0.00012662,0.00000748896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000574284,"about_ca_system_score_gemma":0.00003576015,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00614793,"about_ca_topic_score_gemma":0.440333,"domain_scores_codex":[0.9988189,0.000120492,0.0003038438,0.0003553091,0.0001450944,0.000256366],"domain_scores_gemma":[0.9995386,0.0001296849,0.00008190596,0.00003888907,0.00007136114,0.0001395529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001913682,0.0002626101,0.8111325,0.00003188545,0.000004938187,0.000002044506,0.00008149414,0.000002508021,0.1860731,0.001502869,0.0003539139,0.0003608049],"study_design_scores_gemma":[0.0005139147,0.0005731071,0.9942722,0.00003531822,0.000002882182,0.000008622492,0.0001803738,0.0002862706,0.001194655,0.002328921,0.0005022018,0.0001014727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885986,0.000180693,0.000001192805,0.00992646,0.00007603858,0.0003087669,0.0002407449,0.00001031982,0.0006571308],"genre_scores_gemma":[0.9991814,0.0001472711,0.0000414123,0.0004025647,0.0000346392,0.00002706256,0.000160074,5.71083e-7,0.000004934468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4341851,"threshold_uncertainty_score":0.9293872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02192073033422762,"score_gpt":0.2255587963222003,"score_spread":0.2036380659879727,"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."}}