{"id":"W1977622155","doi":"10.1021/es072108l","title":"Anthropogenic Nickel Cycle: Insights into Use, Trade, and Recycling","year":2008,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":257,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; U.S. Geological Survey; National Science Foundation","keywords":"Nickel; Scrap; Material flow analysis; China; Metallurgy; Life-cycle assessment; Materials science; Production (economics); Environmental science; Business; Waste management; Geography; Engineering; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004264031,0.000161471,0.000195415,0.002994974,0.0002481227,0.001096561,0.0001722495,0.0001495842,0.001119495],"category_scores_gemma":[0.0008245234,0.0001055795,0.0003847664,0.004249889,0.0003342279,0.0008534574,0.0004711912,0.0001570126,0.0001123147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001204432,"about_ca_system_score_gemma":0.0009290595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02432652,"about_ca_topic_score_gemma":0.03712009,"domain_scores_codex":[0.9997771,0.00005045758,0.00001619897,0.00002002393,0.000100497,0.00003566569],"domain_scores_gemma":[0.9995509,0.0001266453,0.000118304,0.00002341827,0.0001594553,0.00002125519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001896324,0.00005950556,0.9326716,0.000140241,0.00007011709,0.0003975944,0.0007170485,0.01337558,0.001996731,0.008644874,0.0003741387,0.04136296],"study_design_scores_gemma":[0.000008827177,0.0001203913,0.9507586,0.00003694055,0.00003873372,0.0003857305,0.002705224,0.02538982,0.002524618,0.004651689,0.0133547,0.0000247164],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896337,0.0002468558,0.002020972,0.0001019728,0.000003198145,0.00002667859,0.001123576,0.00002165531,0.006821393],"genre_scores_gemma":[0.9963253,0.0004067987,0.001173346,0.00001448773,0.000004818711,0.00002215037,0.000905298,0.0000117107,0.001136042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02432652,"threshold_uncertainty_score":0.04836982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008453694759029648,"score_gpt":0.230263818059741,"score_spread":0.2218101233007114,"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."}}