{"id":"W2002317194","doi":"10.1002/rem.20067","title":"Modeling remediation time using natural attenuation at a dry-cleaner site","year":2005,"lang":"en","type":"article","venue":"Remediation Journal","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Biorem Technologies (Canada)","funders":"","keywords":"Environmental remediation; Attenuation; Environmental science; Chlorinated solvents; Contamination; Vinyl chloride; Waste management; Natural (archaeology); Environmental chemistry; Environmental engineering; Chemistry; Geology; Engineering; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002625168,0.0003785565,0.0002241679,0.0002628857,0.0002551944,0.0004152633,0.0004562857,0.0006112762,0.0008191437],"category_scores_gemma":[0.00052833,0.0002176801,0.0005068089,0.000248236,0.0002070288,0.0004610731,0.0001670687,0.0002922977,0.0001387328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0013206,"about_ca_system_score_gemma":0.0009258871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05184351,"about_ca_topic_score_gemma":0.03354932,"domain_scores_codex":[0.9999239,0.00001505441,0.000004401612,0.00002548708,0.00001223555,0.00001882594],"domain_scores_gemma":[0.999712,0.0001393618,0.00005188035,0.0000178372,0.00006588506,0.00001299616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001095771,0.0000925902,0.01213645,0.00002958531,0.00001779504,0.00006044123,0.00004095727,0.9757136,0.008509813,0.0002830945,0.00008789082,0.002918188],"study_design_scores_gemma":[0.00002521587,0.0001663871,0.003948019,0.000003038447,0.0000184428,0.00001786089,0.00005417239,0.9878488,0.007525921,0.0001407571,0.0002420987,0.000009340047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934987,0.00003041342,0.00526545,0.00003622038,0.000003222329,0.00001784485,0.0002367989,0.00004190261,0.0008695747],"genre_scores_gemma":[0.9957932,0.00005234894,0.003337876,0.000007258625,9.942016e-7,0.00002014924,0.0001612987,0.000008336201,0.000618534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05184351,"threshold_uncertainty_score":0.1030836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317945926892155,"score_gpt":0.2285444573103959,"score_spread":0.2153649980414743,"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."}}