{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002007983,0.00003808599,0.00004749867,0.00003789905,0.000259146,0.00005095794,0.0001278018,0.000005773907,0.00004756821],"category_scores_gemma":[0.000007731366,0.00003295019,0.00001012536,0.0001289985,0.000005680561,0.0001714552,0.0003130208,0.00007502729,0.000007778639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001390398,"about_ca_system_score_gemma":0.00001303542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001228178,"about_ca_topic_score_gemma":0.000009781671,"domain_scores_codex":[0.9995289,0.00007393734,0.0000638921,0.0001413785,0.0001181486,0.00007373675],"domain_scores_gemma":[0.9997916,0.00002786776,0.00002904638,0.000115694,0.00001144054,0.0000243461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004435071,0.00002879078,0.0158473,0.00001137414,0.00001568408,0.00001598351,0.007241408,0.001563499,0.001601236,0.9128814,0.01172348,0.04906537],"study_design_scores_gemma":[0.0008641139,0.0004283563,0.0172422,0.000008572408,0.000005174122,0.0001996971,0.002629988,0.8075764,0.0008457397,0.01817963,0.1515979,0.00042216],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.326962,0.0001448854,0.6226666,0.005870194,0.0008113089,0.0002223558,9.092221e-7,0.0002692281,0.04305257],"genre_scores_gemma":[0.9900176,4.101348e-7,0.004708436,0.0005177826,0.00002073147,0.00001772131,8.818641e-7,0.000002356654,0.004714071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8947018,"threshold_uncertainty_score":0.1993168,"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."}}