{"id":"W4392546581","doi":"10.2139/ssrn.4751204","title":"Atr-Ftir Spectroscopy and Machine/Deep Learning Models for Detecting Adulteration in Coconut Water with Sugars, Sugar Alcohols, and Artificial Sweeteners","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Coconut Research and Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Canadian Food Inspection Agency","funders":"","keywords":"Sugar; Artificial Sweetener; Fourier transform infrared spectroscopy; Chemistry; Food science; Chemical engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004410708,0.0009187952,0.0003879947,0.0006467726,0.0001925751,0.0005158192,0.0004934756,0.0007662581,0.001186351],"category_scores_gemma":[0.0007868298,0.000263818,0.0004513023,0.0004926943,0.0002103142,0.0008564648,0.0003297595,0.0007876048,0.0004133149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004503074,"about_ca_system_score_gemma":0.0003656702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006009523,"about_ca_topic_score_gemma":0.006642966,"domain_scores_codex":[0.9998983,0.00001715129,0.000003957424,0.00003870851,0.00002226039,0.00001955973],"domain_scores_gemma":[0.9997748,0.00009110625,0.00003707126,0.00001959282,0.0000603328,0.0000171441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001195093,0.0008151312,0.01617933,0.0003176386,0.0001919385,0.0002442749,0.00009653969,0.3346336,0.2650598,0.002535506,0.002580054,0.3761511],"study_design_scores_gemma":[0.000004659987,0.00003290841,0.000859932,0.000002457149,0.0000123299,0.00001175184,0.000008376057,0.981432,0.01715085,0.0003587069,0.0001208785,0.000005100068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7647902,0.001832037,0.2271377,0.0004794557,0.000113208,0.00005270023,0.0004954994,0.001921917,0.003177173],"genre_scores_gemma":[0.9285772,0.0005607925,0.06670471,0.0000795316,0.00003306671,0.00002918149,0.0003780234,0.00007468972,0.003562685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006009523,"threshold_uncertainty_score":0.01194906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861257827744684,"score_gpt":0.2737735198352114,"score_spread":0.2551609415577646,"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."}}