{"id":"W4206974297","doi":"10.1016/j.foodchem.2022.132219","title":"Untargeted analysis of microbial metabolites and unsaturated fatty acids in salmon via hydrophilic-lipophilic balanced solid-phase microextraction arrow","year":2022,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Sponsorship Council","keywords":"Food spoilage; Solid-phase microextraction; Chemistry; Squalene; Food science; Chromatography; Nutrient; Residue (chemistry); Bacteria; Gas chromatography–mass spectrometry; Biochemistry; Organic chemistry; Biology; Mass spectrometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001988336,0.0003367659,0.0001658992,0.0001174987,0.0001498242,0.0002221968,0.0001215537,0.0003033483,0.0006677287],"category_scores_gemma":[0.0001950135,0.0001708246,0.0001946239,0.00009530634,0.0001740083,0.0001985008,0.0003024438,0.0004598689,0.0004712599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001611169,"about_ca_system_score_gemma":0.0004157523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166163,"about_ca_topic_score_gemma":0.004990287,"domain_scores_codex":[0.9998428,0.00001912416,0.000008376171,0.00005279685,0.00005405105,0.00002293284],"domain_scores_gemma":[0.9999094,0.00002331443,0.00001479127,0.000008996213,0.00003479904,0.000008693274],"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":[0.00003538889,0.000003738836,0.0001070929,0.00001313694,0.000002183891,0.000006536249,0.000005768797,0.00002064822,0.9989939,0.0000131415,0.000008907356,0.0007895625],"study_design_scores_gemma":[0.000005282548,0.0001462442,0.001413793,0.000002972876,0.0000079719,0.00002599247,0.00002231382,0.0006576664,0.9969835,0.00002218824,0.0007079908,0.000004247525],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606689,0.001002886,0.03489092,0.0001275527,0.00006309515,0.0000857995,0.00087967,0.0001505469,0.002130576],"genre_scores_gemma":[0.9465141,0.0008662649,0.03940917,0.0001988059,0.0000157448,0.0001026524,0.0009279106,0.00005184717,0.01191338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001166163,"threshold_uncertainty_score":0.00231874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01671336866389895,"score_gpt":0.2592853085282942,"score_spread":0.2425719398643953,"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."}}