{"id":"W2142408381","doi":"10.1002/rem.21345","title":"Integrating Remediation and Reuse to Achieve Whole‐System Sustainability Benefits","year":2013,"lang":"en","type":"article","venue":"Remediation Journal","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Pacific Railway (Canada)","funders":"Albert Einstein College of Medicine, Yeshiva University; Washington State University","keywords":"Reuse; Environmental remediation; Sustainability; Context (archaeology); Redevelopment; Life-cycle assessment; Exploit; Process (computing); Environmental planning; Business; Environmental science; Process management; Computer science; Engineering; Waste management; Civil engineering; Computer security; Production (economics); Economics; Geography","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":[0.00141474,0.00008376239,0.0001210122,0.00009820119,0.0008812413,0.000239731,0.0001556027,0.00008986456,0.00007326581],"category_scores_gemma":[0.002156206,0.00007774046,0.0000279599,0.0001500485,0.0000716665,0.0007312462,0.00004937954,0.000234002,0.00006675735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007562434,"about_ca_system_score_gemma":0.0002027207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005271639,"about_ca_topic_score_gemma":0.0009196831,"domain_scores_codex":[0.9984842,0.0002538066,0.0003471648,0.0001429057,0.0004608107,0.0003111217],"domain_scores_gemma":[0.9988705,0.0001761825,0.0001871807,0.00012294,0.000244082,0.0003991325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001020587,0.0001886074,0.3440005,0.0009268552,0.00004184562,0.00001157905,0.2805232,0.0006226439,0.001399034,0.06498228,0.02270494,0.2844964],"study_design_scores_gemma":[0.0005491272,0.0002683907,0.5833553,0.0003228986,0.00003995841,0.00001452843,0.393586,0.0005225461,0.00006244986,0.004893929,0.01606167,0.0003232827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611162,0.000424982,0.000735681,0.03520724,0.0005172322,0.0005106509,0.000003422703,0.00004387988,0.00144071],"genre_scores_gemma":[0.9957308,0.000770269,0.001553144,0.0005923558,0.0010824,0.00002890594,0.0000046971,0.000008480622,0.000228961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2841731,"threshold_uncertainty_score":0.6777885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01519992702487768,"score_gpt":0.2904736649005115,"score_spread":0.2752737378756339,"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."}}