{"id":"W3007663661","doi":"10.1051/e3sconf/20199812003","title":"Use of C–Cl CSIA to elucidate origin and fate of DCM in complex contaminated field sites","year":2019,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo","funders":"Agencia Estatal de Investigación; European Regional Development Fund; Universitat Autònoma de Barcelona; Generalitat de Catalunya; European Commission","keywords":"Microcosm; Dichloromethane; Environmental chemistry; Contamination; Isotope analysis; Pollutant; Chloroform; Chemistry; Groundwater; Environmental science; Solvent; Geology; Ecology; Chromatography; Biology; Organic chemistry","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":[0.0003294553,0.0004665609,0.0004074616,0.001141915,0.0005964857,0.0007191354,0.0004794428,0.0004777837,0.000732666],"category_scores_gemma":[0.0005140302,0.0002699335,0.0002607258,0.0008054367,0.0003712132,0.0002788741,0.0004465605,0.000463582,0.0003643107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001398279,"about_ca_system_score_gemma":0.001093934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04073516,"about_ca_topic_score_gemma":0.06233875,"domain_scores_codex":[0.9995824,0.00003281292,0.0000133337,0.0002020217,0.00009020376,0.00007922918],"domain_scores_gemma":[0.9996585,0.0000547213,0.0000574806,0.0000371795,0.000129597,0.00006251896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003813689,0.00004747423,0.01891667,0.00005026084,0.00001896275,0.00007183177,0.0001171884,0.000926577,0.973992,0.00005986134,0.00006131611,0.005356445],"study_design_scores_gemma":[0.00007617878,0.0004974274,0.1729688,0.00002474468,0.0000789325,0.0001801051,0.0004907836,0.02235886,0.7991475,0.0001773999,0.003937869,0.00006126527],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928384,0.0002771037,0.003347461,0.0000447137,0.00001037538,0.00003877554,0.00113112,0.00009275015,0.002219299],"genre_scores_gemma":[0.9920191,0.0001631732,0.006654012,0.00005228111,0.000004195986,0.0000325109,0.000419469,0.00002575688,0.0006294739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04073516,"threshold_uncertainty_score":0.0809961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03939040914469535,"score_gpt":0.2568496323261623,"score_spread":0.2174592231814669,"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."}}