{"id":"W4306402923","doi":"10.3390/su142013220","title":"A Transformer-Based Machine Learning Approach for Sustainable E-Waste Management: A Comparative Policy Analysis between the Swiss and Canadian Systems","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Software deployment; Data envelopment analysis; Electronic waste; Environmental economics; Sustainable management; Policy analysis; Business; Environmental planning; Engineering; Economics; Sustainability; Public administration; Waste management; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004559725,0.0004016093,0.0004020115,0.003637583,0.001447618,0.002487981,0.0009331604,0.0005213704,0.002690354],"category_scores_gemma":[0.01069635,0.0001884886,0.000719437,0.005349058,0.001302245,0.001701571,0.0009736221,0.000730597,0.0001264677],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04064403,"about_ca_system_score_gemma":0.03254389,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8889444,"about_ca_topic_score_gemma":0.888203,"domain_scores_codex":[0.9965432,0.001599916,0.0000795741,0.0002119893,0.00104838,0.0005169157],"domain_scores_gemma":[0.9960859,0.002091058,0.0002333652,0.0001996914,0.001291879,0.00009813762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003688883,0.0002136957,0.03443204,0.0002938873,0.0001840682,0.0001484719,0.000836034,0.6057922,0.001818236,0.2430087,0.002726655,0.1101773],"study_design_scores_gemma":[0.00003832858,0.0001625888,0.03435117,0.00008632521,0.0001270478,0.0000487643,0.00299088,0.9264348,0.00274009,0.02040024,0.01253763,0.00008207506],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8009967,0.001507982,0.1091268,0.003576226,0.00002827293,0.0004271967,0.002171227,0.0002666278,0.08189901],"genre_scores_gemma":[0.9767754,0.0007908217,0.01954865,0.00006066925,0.000005687325,0.0001015635,0.0005221383,0.00002913681,0.002165886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.959356,"threshold_uncertainty_score":0.2948945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276339079607284,"score_gpt":0.2605169604908377,"score_spread":0.2477535696947648,"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."}}