{"id":"W4378835431","doi":"10.20944/preprints202305.2163.v1","title":"Real Time Deployment of MobileNetV3 Model in Edge Computing Devices Using Rgb Color Images for Varietal Classification of Chickpea","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"GABA and Rice Research","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Centers for Disease Control and Prevention; Indian Council of Agricultural Research","keywords":"RGB color model; Artificial intelligence; Computer science; Android (operating system); Classifier (UML); Software deployment; Mobile phone; Raspberry pi; Android application; Computer vision; Embedded system; Internet of Things; Operating system","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":[0.001264412,0.0002155583,0.0004863218,0.00006573754,0.00009626176,0.00001788286,0.0006085545,0.0002818324,0.00004999944],"category_scores_gemma":[0.0001312874,0.0001080182,0.0002062427,0.0002692732,0.0001228215,0.00006364381,0.001200781,0.0003073055,0.0000269474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000998629,"about_ca_system_score_gemma":0.00009860986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001917969,"about_ca_topic_score_gemma":0.0001930293,"domain_scores_codex":[0.9977662,0.0001512229,0.0006823299,0.0006838188,0.0003588204,0.000357592],"domain_scores_gemma":[0.9985964,0.0003879517,0.0004819805,0.0001997262,0.000257117,0.00007684495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005935314,0.0002019551,0.1420483,0.0002765959,0.00004037079,7.559228e-7,0.0002160622,0.0171684,0.8385593,0.00005428642,0.000007797986,0.001366827],"study_design_scores_gemma":[0.000128107,0.00004345302,0.7363571,0.0001940118,0.00002578046,5.903884e-7,0.0001617791,0.226482,0.03593623,0.0005055466,0.000008520212,0.0001568371],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979457,0.00003688173,0.0000908884,0.0001847224,0.0000869463,0.001102554,0.0001456734,0.00006418821,0.0003424179],"genre_scores_gemma":[0.9984671,0.0001183823,0.0008671597,0.000003966957,0.00009515461,0.00007665343,0.0001456478,0.000005116449,0.0002207468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8026231,"threshold_uncertainty_score":0.4404856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2928785148654588,"score_gpt":0.3967014997136272,"score_spread":0.1038229848481684,"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."}}