{"id":"W4399420659","doi":"10.1016/j.fct.2024.114806","title":"Contamination of trace, non-essential/heavy metals in nutraceuticals/dietary supplements: A chemometric modelling approach and evaluation of human health risk upon dietary exposure","year":2024,"lang":"en","type":"article","venue":"Food and Chemical Toxicology","topic":"Heavy Metals in Plants","field":"Chemistry","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sheridan College","funders":"King Saud University","keywords":"Nutraceutical; Heavy metals; Human health; Contamination; Environmental health; Food science; Dietary supplement; Health risk; TRACE (psycholinguistics); Risk assessment; Environmental chemistry; Environmental science; Medicine; Chemistry; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.001705697,0.0002134276,0.0006713857,0.0002798858,0.00004348622,0.00001468814,0.00011997,0.0003409495,0.00009520451],"category_scores_gemma":[0.0001498029,0.0002094108,0.00008143912,0.0003852374,0.000141536,0.0001182663,0.00007890607,0.0004026995,5.293656e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009267706,"about_ca_system_score_gemma":0.00008794822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003353153,"about_ca_topic_score_gemma":0.0000145719,"domain_scores_codex":[0.9977319,0.0001721811,0.0008379159,0.0005155827,0.0004223943,0.0003200899],"domain_scores_gemma":[0.9990493,0.0003313861,0.0002124583,0.0002027211,0.00008512255,0.0001189979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001554935,0.001107406,0.001763192,0.003777938,0.0004135084,0.00000377204,0.001211674,0.0003827121,0.9709314,0.0002405283,0.00007536346,0.01993706],"study_design_scores_gemma":[0.002122387,0.000556387,0.001297973,0.000258255,0.0003970176,0.00002500589,0.0005037871,0.138955,0.8536444,0.001918294,0.00005731197,0.0002641806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878287,0.01075222,0.0003117934,0.00009198729,0.00005727175,0.0003206532,0.0001865578,0.00002309998,0.0004277142],"genre_scores_gemma":[0.9978461,0.0007126064,0.001033945,0.00001471187,0.00006622562,0.00006607465,0.0002263559,0.00002238447,0.00001160532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1385722,"threshold_uncertainty_score":0.8539523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06475232678182286,"score_gpt":0.3445682196133286,"score_spread":0.2798158928315058,"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."}}