{"id":"W2189072119","doi":"","title":"INTELLIGENT COMPUTER VISION SYSTEM (SAIF) FOR AUTOMATED INSPECTION OF GINSENG ROOTS QUALITY","year":2005,"lang":"en","type":"article","venue":"","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Thresholding; Process (computing); Software; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001027111,0.0007812429,0.0009149309,0.001159209,0.0004932943,0.000650283,0.0009357166,0.0009392425,0.005898605],"category_scores_gemma":[0.001036263,0.0003202894,0.0003520294,0.000515774,0.0002678843,0.000530576,0.0004586547,0.0006764998,0.001930609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006028868,"about_ca_system_score_gemma":0.0006920347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001489983,"about_ca_topic_score_gemma":0.001478078,"domain_scores_codex":[0.9992926,0.0001128734,0.00003890653,0.0001754969,0.0003210205,0.00005904406],"domain_scores_gemma":[0.9992959,0.0001148221,0.00005689408,0.00006696452,0.0004150572,0.00005031977],"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":[0.00113299,0.0003409368,0.00579966,0.0006486004,0.0001016579,0.0002507866,0.0003149456,0.00720158,0.3591101,0.00287751,0.02112424,0.6010969],"study_design_scores_gemma":[0.000564274,0.003671568,0.0313559,0.0001918205,0.000387043,0.003427935,0.0001687544,0.5463132,0.3063478,0.002454265,0.1048276,0.0002898213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03587379,0.0006434095,0.9377451,0.0001683123,0.0001674471,0.0004902536,0.0003919777,0.01886947,0.00565024],"genre_scores_gemma":[0.369819,0.0005187044,0.6135008,0.0003637607,0.0001135456,0.001015867,0.001556883,0.0003179274,0.01279343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005898605,"threshold_uncertainty_score":0.01973277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02624415418336703,"score_gpt":0.3482568052121535,"score_spread":0.3220126510287865,"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."}}