{"id":"W4379875209","doi":"10.1109/icaaic56838.2023.10141483","title":"Automated Garbage Classification using Deep Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Garbage; Computer science; Sorting; Process (computing); Task (project management); Deep learning; Artificial intelligence; Bottleneck; Contextual image classification; Automation; Waste management; Engineering; Image (mathematics); Embedded system; Systems engineering","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":[0.0003002629,0.001113242,0.0005967731,0.001572924,0.0003410441,0.0007446422,0.0009080293,0.0006297643,0.002286718],"category_scores_gemma":[0.000428931,0.0004267771,0.0007743572,0.0009612921,0.0003062095,0.0007844603,0.0007689862,0.0006600721,0.001273858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008044484,"about_ca_system_score_gemma":0.001177136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009096664,"about_ca_topic_score_gemma":0.01515274,"domain_scores_codex":[0.9997589,0.00001855063,0.00001188268,0.00007132828,0.00006596321,0.00007339181],"domain_scores_gemma":[0.999822,0.00002596499,0.00003074812,0.00002866125,0.00007958687,0.00001304304],"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":[0.0004288112,0.0003171093,0.007379488,0.0002503073,0.0001265637,0.0003313347,0.00007764579,0.1594074,0.05684955,0.00190979,0.008671672,0.7642503],"study_design_scores_gemma":[0.000008375924,0.0000587269,0.002136247,0.00003338161,0.00002823302,0.00005813028,0.00004063182,0.9636692,0.02971129,0.001406074,0.002830356,0.00001920593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.306257,0.001769069,0.6639103,0.0004770326,0.0003216235,0.0001742123,0.001901634,0.01390254,0.01128655],"genre_scores_gemma":[0.875333,0.000818481,0.1077434,0.0002319937,0.00005183876,0.0001036326,0.003164179,0.0001723231,0.0123811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009096664,"threshold_uncertainty_score":0.01808739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0355452362645881,"score_gpt":0.2574263930201213,"score_spread":0.2218811567555332,"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."}}