{"id":"W2025430015","doi":"10.1021/es100828u","title":"A Downhole Passive Sampling System To Avoid Bias and Error from Groundwater Sample Handling","year":2010,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; University of Guelph; Boeing","keywords":"Groundwater; Sampling (signal processing); Sampling error; Environmental science; Sample (material); Petroleum engineering; Computer science; Statistics; Engineering; Observational error; Mathematics; Geotechnical engineering; Telecommunications; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009136848,0.0006565793,0.0005693376,0.001044913,0.000570559,0.0005336278,0.0009475703,0.0004577961,0.004971167],"category_scores_gemma":[0.001642331,0.0004091559,0.0003399155,0.0007028694,0.0004700925,0.0005513195,0.0008842765,0.0006213966,0.000889259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003284386,"about_ca_system_score_gemma":0.001160987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002005657,"about_ca_topic_score_gemma":0.005576251,"domain_scores_codex":[0.9985542,0.0001800628,0.0001389614,0.0003406992,0.0007105286,0.00007566671],"domain_scores_gemma":[0.9983546,0.0002934315,0.0002302593,0.0003597791,0.0006917461,0.00007009739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003066177,0.0002301673,0.00845845,0.0003364308,0.00002059864,0.0001160195,0.0003445834,0.0004077927,0.9116781,0.000946236,0.00275996,0.07439514],"study_design_scores_gemma":[0.0002924205,0.004369596,0.09422674,0.00007964143,0.000240491,0.001341515,0.0002566345,0.01608058,0.7536706,0.001424416,0.1278787,0.0001385772],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3759534,0.0003283656,0.6019865,0.0002577248,0.0004276235,0.004103942,0.003418003,0.004909638,0.00861485],"genre_scores_gemma":[0.4875957,0.0003870257,0.491332,0.0004323585,0.000212013,0.003075225,0.004164142,0.0004626621,0.01233883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004971167,"threshold_uncertainty_score":0.01663023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332731136556488,"score_gpt":0.2263861488803356,"score_spread":0.2130588375147707,"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."}}