{"id":"W4296744480","doi":"10.3390/s22197134","title":"Development of an Intelligent Imaging System for Ripeness Determination of Wild Pistachios","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Ilam University","keywords":"Ripeness; Linear discriminant analysis; Artificial intelligence; Machine vision; Pattern recognition (psychology); Computer science; Artificial neural network; Image processing; Computer vision; Mathematics; Food science; Image (mathematics); Ripening; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001585206,0.00008094639,0.0001809782,0.0001250836,0.000108999,0.000005311866,0.0001475794,0.00001820522,0.000128298],"category_scores_gemma":[0.00002730663,0.00008580174,0.00006021643,0.0002030243,0.00002071235,0.00002802374,0.00004319455,0.00005387887,4.988128e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001838748,"about_ca_system_score_gemma":0.00005035431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002050053,"about_ca_topic_score_gemma":0.000004390281,"domain_scores_codex":[0.9992026,0.00001007927,0.0003159459,0.0001549615,0.0001976705,0.0001187582],"domain_scores_gemma":[0.999481,0.00005276061,0.0002132594,0.0001611312,0.00006281945,0.00002904101],"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":[0.0002009158,0.0004266636,0.004484819,0.002194072,0.0001408287,0.000008782104,0.004311292,0.00190443,0.9573885,0.0007913377,0.00002207076,0.02812633],"study_design_scores_gemma":[0.0001764544,0.00001406472,0.0000749383,0.00001626317,0.00005506248,0.000006907591,0.01138532,0.01209391,0.9753657,0.00001558092,0.00070411,0.00009165948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958648,0.00007649964,0.002856977,0.000006906433,0.00004497711,0.00006427473,0.0000308229,0.00002784397,0.001026863],"genre_scores_gemma":[0.9926344,8.642209e-7,0.006972951,0.000004054871,0.00001781437,0.00002879819,0.00003977482,0.00001298134,0.0002883558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02803467,"threshold_uncertainty_score":0.3498893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896424528474822,"score_gpt":0.2855045582277232,"score_spread":0.266540312942975,"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."}}