{"id":"W2004125248","doi":"10.1007/s11947-009-0292-x","title":"Application of Hyperspectral Technique for Color Classification Avocados Subjected to Different Treatments","year":2009,"lang":"en","type":"article","venue":"Food and Bioprocess Technology","topic":"Postharvest Quality and Shelf Life Management","field":"Agricultural and Biological Sciences","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; McGill University","funders":"","keywords":"Hyperspectral imaging; Spectroradiometer; Color discrimination; Reflectivity; Coating; Beeswax; Ripening; Shelf life; Horticulture; Materials science; Food science; Chemistry; Biology; Wax; Artificial intelligence; Computer science; Optics; Nanotechnology; Color vision; Composite material","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":[0.00007338922,0.0001079994,0.0001694847,0.00005325969,0.00009100836,0.00001333676,0.0001723197,0.0001526893,0.000002303586],"category_scores_gemma":[0.00002454101,0.00004674568,0.00003213715,0.0004119656,0.00004957427,0.00003681381,0.00002534294,0.00004447446,0.000001377648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002008539,"about_ca_system_score_gemma":0.000002754265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001016758,"about_ca_topic_score_gemma":0.00006808237,"domain_scores_codex":[0.9992965,0.000009961188,0.0001820462,0.0002691103,0.0000732622,0.0001691309],"domain_scores_gemma":[0.9997242,0.00002282856,0.00008643186,0.00006164991,0.00006336223,0.00004154267],"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":[0.00005818969,0.0002179814,0.001282225,0.00001617841,0.0000117966,8.70771e-8,0.00001994031,1.089948e-7,0.8980256,0.02721729,0.00001425663,0.07313631],"study_design_scores_gemma":[0.0002894747,0.004748301,0.1466831,0.00002090917,0.00003341753,0.000004074614,0.0004536276,0.00006617316,0.8241894,0.02164325,0.001673817,0.0001944211],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868173,0.00006880487,0.001973116,0.009853425,0.00001100928,0.001049143,0.00005303154,0.0001212086,0.00005298558],"genre_scores_gemma":[0.9985023,0.00002167847,0.0008252303,0.0001452179,0.00002459543,0.0003824201,0.00005111145,6.832636e-7,0.00004676411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1454009,"threshold_uncertainty_score":0.1906233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02354808142533286,"score_gpt":0.2613490535709649,"score_spread":0.2378009721456321,"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."}}