{"id":"W4327739947","doi":"10.3390/foods12061273","title":"An Automated Image Processing Module for Quality Evaluation of Milled Rice","year":2023,"lang":"en","type":"article","venue":"Foods","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Artificial intelligence; Solidity; Roundness (object); Random forest; Image processing; Classifier (UML); Computer science; Pattern recognition (psychology); Machine vision; Identification (biology); Perimeter; Mathematics; Machine learning; Image (mathematics)","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":[0.0007223511,0.00008355022,0.0001800758,0.00009743956,0.00007522321,0.00002144446,0.0001316042,0.00007520975,0.0002430511],"category_scores_gemma":[0.0003995434,0.00008035946,0.00006505898,0.0007564402,0.00002877587,0.0001112568,0.00001517101,0.00004431091,0.000008360691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005526948,"about_ca_system_score_gemma":0.00007831025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003169253,"about_ca_topic_score_gemma":0.000003368269,"domain_scores_codex":[0.9990538,0.00002833126,0.0002348439,0.0001966222,0.000323859,0.0001624827],"domain_scores_gemma":[0.9992141,0.00007060398,0.0001448789,0.0002196361,0.0003128784,0.0000379495],"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":[0.00003355443,0.0001213954,0.000999384,0.0004855538,0.00005573518,2.051319e-7,0.0002313091,0.0002296014,0.9949191,0.00002524462,0.0007649646,0.002133943],"study_design_scores_gemma":[0.0006092383,0.0000293004,0.004527209,0.0000101351,0.0001790301,2.910724e-7,0.0004202428,0.3132233,0.6803201,0.000557522,0.00002939655,0.00009425494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949943,0.0001539387,0.0009865123,0.00003626474,0.0000213593,0.00008326412,0.00004397677,0.0004731013,0.003207264],"genre_scores_gemma":[0.997247,0.000003505812,0.00216924,0.000009462617,0.000060029,0.00005613483,0.0001661234,0.00001497715,0.0002735191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.314599,"threshold_uncertainty_score":0.3276964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08778733265688007,"score_gpt":0.4551177888889029,"score_spread":0.3673304562320229,"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."}}