{"id":"W4235776484","doi":"10.32920/ryerson.14661378","title":"Characteristics of cellphones reverse logistics in Canada","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Context (archaeology); Nova scotia; Relevance (law); Computer science; Telecommunications; Business; Geography; Political science; Archaeology","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":[0.0006239786,0.0003801836,0.0002750307,0.002823401,0.005678455,0.004485024,0.001224013,0.000579024,0.01093737],"category_scores_gemma":[0.003174847,0.000254837,0.0003977479,0.00952433,0.001973777,0.0009270961,0.001352007,0.0005455215,0.001253955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06689033,"about_ca_system_score_gemma":0.068492,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9906901,"about_ca_topic_score_gemma":0.9950342,"domain_scores_codex":[0.9974182,0.00008689717,0.00008221987,0.0002172047,0.001327669,0.0008679277],"domain_scores_gemma":[0.9942966,0.0003698045,0.0005821038,0.0001066475,0.003961985,0.0006828966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006446621,0.0002199376,0.7450383,0.0007611937,0.00008122923,0.004014563,0.0318739,0.005517467,0.009444933,0.02212304,0.02460548,0.1556754],"study_design_scores_gemma":[0.0000122675,0.0001217002,0.7465089,0.000255836,0.00005332,0.001195472,0.1021296,0.002620806,0.003426228,0.0008018534,0.1427109,0.0001631595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9059891,0.001161212,0.001063532,0.001357102,0.00002817376,0.0001808935,0.004702753,0.00009789388,0.0854193],"genre_scores_gemma":[0.9590526,0.001419054,0.001123549,0.0002172473,0.000005321678,0.00003172243,0.001783269,0.00004068792,0.03632645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06689033,"threshold_uncertainty_score":0.4853256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291731670412326,"score_gpt":0.209441039791024,"score_spread":0.1965237230869007,"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."}}