{"id":"W3148564872","doi":"10.3390/foods10040717","title":"Spatial Fingerprinting: Horizontal Fusion of Multi-Dimensional Bio-Tracers as Solution to Global Food Provenance Problems","year":2021,"lang":"en","type":"article","venue":"Foods","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada First Research Excellence Fund","keywords":"Provenance; Computer science; Identification (biology); Sensor fusion; Data science; Data mining; Biology; Ecology; Machine learning","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":[0.003777521,0.0005388416,0.0007996682,0.001118594,0.0004736532,0.001233724,0.001072835,0.0008762464,0.0009097258],"category_scores_gemma":[0.008027163,0.0003870576,0.0008349984,0.001760607,0.001290521,0.002465091,0.002674129,0.001055949,0.0001976332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008722774,"about_ca_system_score_gemma":0.001095664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003397783,"about_ca_topic_score_gemma":0.002175224,"domain_scores_codex":[0.9989297,0.0004074116,0.00005130439,0.0002481014,0.0002641892,0.00009920541],"domain_scores_gemma":[0.9967464,0.001595377,0.0005458732,0.0006621212,0.0003229954,0.0001271961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006990688,0.0002187765,0.03508176,0.000292164,0.00024232,0.0002486724,0.0005755884,0.5517732,0.04362946,0.0856429,0.001033903,0.2805622],"study_design_scores_gemma":[0.00002668435,0.0001509266,0.004080075,0.00002457213,0.00003443198,0.00009507873,0.0001051334,0.9386321,0.01033258,0.0447593,0.001722767,0.00003632077],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09292296,0.0003301649,0.9047555,0.0002380882,0.00003292827,0.00003480519,0.0001971317,0.000404194,0.001084232],"genre_scores_gemma":[0.7517521,0.0002248065,0.2469492,0.00009539156,0.0000242297,0.00005525327,0.0003020657,0.00006017739,0.0005369125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003777521,"threshold_uncertainty_score":0.01997769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02150927254913505,"score_gpt":0.2810863632678051,"score_spread":0.2595770907186701,"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."}}