{"id":"W7115572519","doi":"10.1016/j.foodchem.2025.147610","title":"Rapid, non-destructive and comprehensive quantitative analysis of honey by combined use of conventional and broadband-WET NMR spectra","year":2025,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Bee Products Chemical Analysis","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Quantitative analysis (chemistry); Tryptophan; Proton NMR; NMR spectra database; Carbon-13 NMR; Quantitative assessment","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":[0.00004688304,0.0001328327,0.0004421563,0.00002104026,0.00004857568,0.00001898241,0.0001031393,0.00008863318,0.000156737],"category_scores_gemma":[0.00007450225,0.00006751421,0.0001298877,0.0008267254,0.0003483805,0.00006487502,0.00008805787,0.0000931626,2.144736e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001097559,"about_ca_system_score_gemma":0.000007873021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001217741,"about_ca_topic_score_gemma":0.0000177184,"domain_scores_codex":[0.9991145,0.00002399914,0.0002722134,0.0003296109,0.0001392135,0.0001204546],"domain_scores_gemma":[0.9991662,0.0003269278,0.0001801799,0.00006772324,0.0002000057,0.00005899254],"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":[0.00009471704,0.0000963799,0.00797285,0.00006331143,0.00134944,2.720989e-7,0.00003536581,0.000002602255,0.9893631,0.0001470386,0.0003514703,0.0005234868],"study_design_scores_gemma":[0.0003267765,0.000140253,0.05106222,0.00003227867,0.0007338143,7.318193e-7,0.0003841764,0.0003028442,0.9459304,0.000669892,0.0002801791,0.0001364273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980408,0.0008048985,0.000007155273,0.0003968021,0.000008085467,0.00006704138,0.000508193,0.00000865665,0.0001583664],"genre_scores_gemma":[0.9990793,0.0001380287,0.0002928506,0.00003415632,0.000009197752,0.000003580596,0.0002940421,6.330327e-7,0.0001482524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04343266,"threshold_uncertainty_score":0.275315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01971041382898596,"score_gpt":0.2255657263708158,"score_spread":0.2058553125418298,"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."}}