{"id":"W4306954521","doi":"10.1016/j.foodchem.2022.134680","title":"Development of an automated solid phase extraction instrument for determination of lead in high-salt foods","year":2022,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Dye analysis and toxicity","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Reproducibility; Chromatography; Extraction (chemistry); Solid phase extraction; Chemistry; Matrix (chemical analysis); Reagent; Adsorption; Relative standard deviation; Accuracy and precision; Detection limit; Mathematics","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":[0.0002004655,0.0001272755,0.0002604699,0.00004791209,0.00007906763,0.000007501518,0.0001829845,0.00008167361,0.0003321718],"category_scores_gemma":[0.00002865507,0.000149699,0.00007920722,0.000151067,0.00002168451,0.00008087682,0.00006733189,0.0001239881,2.599424e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002050771,"about_ca_system_score_gemma":0.0001291876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001259572,"about_ca_topic_score_gemma":0.00002163668,"domain_scores_codex":[0.9987294,0.00001050687,0.0005720383,0.0002444017,0.000276079,0.0001675743],"domain_scores_gemma":[0.9992474,0.00002548097,0.0003875442,0.0002369688,0.00006237227,0.00004019454],"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":[0.0001139711,0.00114116,0.00005888035,0.0003862581,0.00004938482,0.000001390089,0.0002732559,0.00009678725,0.9782362,0.000005537175,0.00001117113,0.01962601],"study_design_scores_gemma":[0.001730677,0.0001102546,0.00004808374,0.0000260099,0.00003312678,0.000004120735,0.000506865,0.02181702,0.9751972,0.00006279178,0.0003244742,0.0001394023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987894,0.00001774783,0.0004150533,0.00001121449,0.00002597097,0.00006583546,0.0001255536,0.00005651331,0.0004926557],"genre_scores_gemma":[0.9931866,0.000001329963,0.006024283,0.000004372315,0.00002837702,0.00012117,0.000506444,0.00001608926,0.0001113237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02172024,"threshold_uncertainty_score":0.610455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02360496454482178,"score_gpt":0.3258158029112525,"score_spread":0.3022108383664307,"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."}}