{"id":"W3204164233","doi":"10.1016/j.tifs.2021.09.014","title":"A concise review on food quality assessment using digital image processing","year":2021,"lang":"en","type":"review","venue":"Trends in Food Science & Technology","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":159,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Image processing; Food quality; Artificial intelligence; Machine learning; Feature extraction; Quality (philosophy); Digital image processing; Food processing; Machine vision; Image (mathematics); Food science","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":[0.0007219322,0.001238435,0.001504874,0.003336254,0.0001582959,0.0009654344,0.0007539187,0.0009163927,0.004412935],"category_scores_gemma":[0.00130824,0.0003857917,0.0007185596,0.002994923,0.0003885188,0.001586544,0.0006594502,0.001072656,0.002167536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000370524,"about_ca_system_score_gemma":0.000947838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000894449,"about_ca_topic_score_gemma":0.00165983,"domain_scores_codex":[0.9996951,0.0000452427,0.00005053352,0.00006167322,0.0001271876,0.00002038699],"domain_scores_gemma":[0.999321,0.0003041298,0.0001114681,0.00002039527,0.0002168408,0.00002615662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008164024,0.00005207594,0.0001191679,0.02745881,0.000137678,0.0001074081,0.00002725818,0.0002750215,0.004417719,0.001050302,0.03290116,0.9333717],"study_design_scores_gemma":[0.00003120437,0.0001744718,0.001275997,0.005861907,0.0005494757,0.0008425636,0.0000497319,0.0003784362,0.00337272,0.001431768,0.9859623,0.00006945046],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001513629,0.9970611,0.001083914,0.0002181916,0.0004870635,0.00001474568,0.0000969611,0.00002567702,0.000860994],"genre_scores_gemma":[0.0007497015,0.9960029,0.00128582,0.0003527256,0.0004281173,0.00001908195,0.0001294995,0.000007404554,0.001024791],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004412935,"threshold_uncertainty_score":0.01476276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1576032796140786,"score_gpt":0.4730843709484331,"score_spread":0.3154810913343544,"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."}}