{"id":"W4401694146","doi":"10.1038/s43247-024-01595-1","title":"Overcoming challenges measuring SDG 12 progress using national registers to track chemicals in waste","year":2024,"lang":"en","type":"article","venue":"Communications Earth & Environment","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Environment and Climate Change Canada","funders":"Environment and Climate Change Canada; Queen's University","keywords":"Track (disk drive); Computer science; Environmental science; Business; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.03341977,0.0007915519,0.0008693803,0.008780291,0.001858166,0.007196053,0.003165904,0.001307007,0.002288368],"category_scores_gemma":[0.06444376,0.0005865602,0.0006124919,0.01649319,0.001294106,0.003633835,0.005653868,0.00136722,0.0009981513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01396646,"about_ca_system_score_gemma":0.03269159,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6490002,"about_ca_topic_score_gemma":0.6835172,"domain_scores_codex":[0.9712465,0.01013459,0.003064346,0.002348003,0.01106983,0.002136581],"domain_scores_gemma":[0.9014942,0.01828255,0.01165622,0.01192411,0.05474334,0.001899594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002568062,0.0003233521,0.7434193,0.001028953,0.0003326807,0.00009650367,0.005527281,0.01680172,0.001392636,0.01916937,0.02695427,0.1846971],"study_design_scores_gemma":[0.00009724165,0.0004584087,0.6564708,0.002958073,0.0003657326,0.0001242016,0.02588775,0.04997398,0.01455783,0.01438146,0.2343143,0.0004102386],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6895263,0.002970951,0.06601349,0.01423215,0.0004338715,0.002082984,0.1283728,0.001181937,0.09518549],"genre_scores_gemma":[0.8667526,0.001480535,0.06713009,0.0009295549,0.00008842422,0.001327329,0.05459408,0.0002051078,0.007492156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6490002,"threshold_uncertainty_score":0.7061337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1086228568930778,"score_gpt":0.3069035058160731,"score_spread":0.1982806489229952,"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."}}