{"id":"W2898262301","doi":"10.1111/gwmr.12303","title":"Special Issue: Diagnostic Tools to Assess In Situ Remediation System Performance","year":2018,"lang":"en","type":"article","venue":"Groundwater Monitoring & Remediation","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Environmental remediation; Environmental science; Soil vapor extraction; Air sparging; Contamination; Zerovalent iron; Groundwater remediation; Waste management; Environmental chemistry; Biochemical engineering; Chemistry; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006720887,0.0002206115,0.0001999004,0.0001390083,0.0001666261,0.0001664763,0.0002767565,0.0001506681,0.0004448172],"category_scores_gemma":[0.0003908839,0.0002099597,0.00003710783,0.0005738557,0.00006570542,0.0008623142,0.0001387355,0.0001500019,0.005768482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121392,"about_ca_system_score_gemma":0.00001988645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001492193,"about_ca_topic_score_gemma":0.0003449344,"domain_scores_codex":[0.997803,0.00009973125,0.0005004197,0.0004747245,0.0006464534,0.000475684],"domain_scores_gemma":[0.9991962,0.0001451857,0.000155548,0.0002809272,0.00005350262,0.0001686682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006013253,0.00007781485,0.6585718,0.00003455711,0.000005585013,0.000007325546,0.002261691,0.0001010726,0.2823006,0.000005130245,0.004615948,0.05195836],"study_design_scores_gemma":[0.0003637077,0.0001513001,0.7618464,0.00007956605,0.000008644132,0.000002561284,0.0001672601,0.0000965969,0.2101414,0.0000027952,0.02688126,0.0002584822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986764,0.000003004349,0.0002179068,0.0002100792,0.007272951,0.0005439634,0.000003846964,0.0001034975,0.004880757],"genre_scores_gemma":[0.9812095,0.00003042913,0.0008029716,0.00007824092,0.01735966,0.00003638886,0.00003230881,0.00002298687,0.0004275492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1032747,"threshold_uncertainty_score":0.9950057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675113678605047,"score_gpt":0.2488946507261119,"score_spread":0.2221435139400614,"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."}}