{"id":"W3089708326","doi":"10.1101/2020.10.01.322453","title":"Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Provenance; Generality; Computer science; Data science; Biology; Paleontology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000351362,0.0004348951,0.0003815111,0.0001025065,0.0001574254,0.00009339593,0.0005443307,0.0005528221,0.00001793916],"category_scores_gemma":[0.0004245967,0.0005030385,0.0002108734,0.0003434329,0.0001248274,0.00001095313,0.000712877,0.0003063374,0.00008546625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001280413,"about_ca_system_score_gemma":0.0006952389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001346788,"about_ca_topic_score_gemma":0.00002496789,"domain_scores_codex":[0.997114,0.0001125031,0.0007114224,0.001254677,0.0004206987,0.0003866691],"domain_scores_gemma":[0.9973648,0.000008708905,0.0006581721,0.0009687008,0.000726738,0.000272875],"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":[0.00008841785,0.0002300462,0.001463897,0.000239423,0.0001126923,0.000001521049,0.0000106715,0.000239233,0.9964971,0.0005889729,0.000514393,0.00001362358],"study_design_scores_gemma":[0.0005453922,0.0003630306,0.03075897,0.0002149663,0.00005729715,4.261385e-8,0.000003562767,0.0009219641,0.9602451,0.000002755246,0.006310761,0.0005761542],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737317,0.0005452253,0.02171488,0.0006638718,0.001421996,0.001279105,0.0005156343,0.0001140956,0.00001348542],"genre_scores_gemma":[0.9918756,0.00005505511,0.00727208,0.0001653409,0.0003446713,0.0001986382,0.00001221383,0.00006713878,0.000009223601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.036252,"threshold_uncertainty_score":0.9997422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02098503909403793,"score_gpt":0.2460492990596095,"score_spread":0.2250642599655716,"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."}}