{"id":"W4315836086","doi":"10.1109/iconsip49665.2022.10007497","title":"Smart and Lucrative Waste Segregation","year":2022,"lang":"en","type":"article","venue":"","topic":"Smart Systems and Machine Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Triple Point Technology (Canada)","funders":"","keywords":"Garbage; Process (computing); Identification (biology); Computer science; Municipal solid waste; Plastic waste; Waste management; Risk analysis (engineering); Engineering; Business; Operating system","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":[0.0006964424,0.0005425624,0.0006187503,0.001111277,0.0006518358,0.001502403,0.001264494,0.0007966817,0.004651773],"category_scores_gemma":[0.001656225,0.0004105171,0.0003661343,0.0007146152,0.000971168,0.002116929,0.002000758,0.0006133959,0.002832195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003540026,"about_ca_system_score_gemma":0.0006534275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006630367,"about_ca_topic_score_gemma":0.001471022,"domain_scores_codex":[0.999103,0.0001235892,0.00004483947,0.0002229133,0.0004182415,0.0000874595],"domain_scores_gemma":[0.9990609,0.0002094639,0.0001534352,0.0003528465,0.000167755,0.00005552576],"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":[0.0006344366,0.0005350655,0.006671669,0.0003752769,0.000055375,0.0003178914,0.0008665743,0.02215008,0.213266,0.0276752,0.006626581,0.720826],"study_design_scores_gemma":[0.0001875065,0.0009709363,0.01101644,0.0002083735,0.0001435854,0.001264638,0.000635441,0.2863443,0.4518555,0.04296429,0.2041211,0.0002879464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08805884,0.0003504572,0.8823801,0.0005647111,0.0001424103,0.000274278,0.0001480685,0.009287356,0.01879364],"genre_scores_gemma":[0.4541082,0.0003643224,0.5197932,0.0006459334,0.0000847677,0.0001977107,0.0002672402,0.0005757402,0.02396289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004651773,"threshold_uncertainty_score":0.01556176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006906644845144665,"score_gpt":0.2096374035345305,"score_spread":0.2027307586893858,"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."}}