{"id":"W6990941647","doi":"","title":"Evaluation of Machine Learning Techniques for Image Based Quality Assessment of Chickpea","year":2022,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Hyperspectral imaging; Random forest; Pattern recognition (psychology); Convolutional neural network; Mean squared error; Artificial neural network; Classifier (UML)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002545938,0.0009115075,0.0004597974,0.001015361,0.0001815569,0.0006860989,0.0006536455,0.0006330856,0.0007399879],"category_scores_gemma":[0.004252725,0.00013556,0.0006073687,0.0006281928,0.0001722921,0.0005986454,0.000364306,0.0006876103,0.0003177904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006441041,"about_ca_system_score_gemma":0.00052123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004262954,"about_ca_topic_score_gemma":0.003167409,"domain_scores_codex":[0.9992886,0.0001979642,0.0000583081,0.0001262629,0.0002749691,0.00005404397],"domain_scores_gemma":[0.9981774,0.0008162272,0.0001750347,0.0001046428,0.0006886594,0.00003803677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007016172,0.0003863509,0.01598523,0.0004236017,0.0003583898,0.0001715586,0.0001188108,0.2872479,0.04103862,0.001460938,0.002644895,0.649462],"study_design_scores_gemma":[0.00001014014,0.0002049413,0.005788632,0.0000219654,0.00003647429,0.00004851132,0.00003440421,0.9817864,0.01109251,0.0003591283,0.0006073728,0.000009522102],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5475976,0.00524165,0.4367732,0.0006489751,0.000233517,0.000268281,0.0006635656,0.002714022,0.005859165],"genre_scores_gemma":[0.8380042,0.001173123,0.1576952,0.00009685528,0.00003172864,0.00011274,0.0007663897,0.00007989003,0.002039846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004262954,"threshold_uncertainty_score":0.01346439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03830472784640824,"score_gpt":0.3474720750804475,"score_spread":0.3091673472340392,"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."}}