{"id":"W4389042690","doi":"10.1016/j.foodchem.2023.138093","title":"Automated sequential SPME addressing the displacement effect in food samples","year":2023,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Narodowe Centrum Nauki","keywords":"Displacement (psychology); Food science; Chemistry; Computer science; Biological system; Biology; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002308533,0.0002933019,0.0003274203,0.00007019793,0.0001836103,0.0001031268,0.0004659854,0.0002077525,0.001437258],"category_scores_gemma":[0.0002153321,0.00022765,0.0001651134,0.001088663,0.0001059724,0.00006060608,0.0001944297,0.0003868115,0.00006170828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001855398,"about_ca_system_score_gemma":0.00006525429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002686027,"about_ca_topic_score_gemma":0.0000147328,"domain_scores_codex":[0.9982482,0.00002342983,0.000341469,0.0004352375,0.0003767608,0.000574933],"domain_scores_gemma":[0.9989553,0.0002837968,0.0001297567,0.0005122633,0.00002533034,0.00009352514],"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":[0.00005572759,0.00007279676,0.003898315,0.0006013273,0.0002847134,0.00002146321,0.0001527905,0.0001497041,0.9903017,0.00001298084,0.004196528,0.0002520065],"study_design_scores_gemma":[0.0007656224,0.00005050507,0.0003876022,0.00008692227,0.000100094,0.000009600484,0.000376623,0.001115929,0.9957494,0.0001083145,0.0009831823,0.0002662668],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894712,0.0005199998,0.00001134828,0.0002176218,0.00005854852,0.00007099645,0.00009398329,0.0008269524,0.008729358],"genre_scores_gemma":[0.998198,0.00002716516,0.00002471885,0.00003925109,0.0002418145,0.00008516214,0.0002465532,0.00003997836,0.001097345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00872682,"threshold_uncertainty_score":0.9994755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05500135408181836,"score_gpt":0.3242687735768955,"score_spread":0.2692674194950772,"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."}}