{"id":"W4413145518","doi":"10.1109/icoeca66273.2025.00189","title":"Waste Management Using Convolutional Neural Network and Object Detection","year":2025,"lang":"en","type":"article","venue":"","topic":"Currency Recognition and Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Object detection; Object (grammar); Artificial neural network; Pattern recognition (psychology)","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":[0.0004869307,0.0008734617,0.0004887091,0.001120821,0.0002679657,0.0008227022,0.0009553482,0.0008570102,0.001171008],"category_scores_gemma":[0.000896554,0.0003601172,0.0005828042,0.001196268,0.0003962657,0.001274938,0.0006509834,0.0006328519,0.0004343224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212155,"about_ca_system_score_gemma":0.0008463564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0180007,"about_ca_topic_score_gemma":0.01689638,"domain_scores_codex":[0.9997644,0.00002210641,0.00001262915,0.00008175783,0.00006595459,0.0000532197],"domain_scores_gemma":[0.999763,0.00006521289,0.00004655669,0.00003099538,0.00008190621,0.00001236821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001866245,0.000169039,0.005517672,0.0001252558,0.0001392767,0.0001913189,0.00004671482,0.5217631,0.02452003,0.005124592,0.00315955,0.4390568],"study_design_scores_gemma":[0.000001412975,0.0000108063,0.0005191374,0.000005487593,0.000009568341,0.00001688557,0.000003867788,0.9933807,0.004294478,0.001219607,0.0005328429,0.000005184338],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1056505,0.001698714,0.8821103,0.0004975863,0.0001663007,0.00006408308,0.0003583824,0.003680235,0.005773787],"genre_scores_gemma":[0.850401,0.0008945158,0.1403118,0.0002178708,0.00006964606,0.00005770057,0.0007241868,0.00009178379,0.007231514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0180007,"threshold_uncertainty_score":0.03579181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02098515604074471,"score_gpt":0.253682549342688,"score_spread":0.2326973933019433,"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."}}