{"id":"W1967795842","doi":"10.1002/rem.21328","title":"The influence of seasonal vertical temperature gradients on no‐purge sampling of wells","year":2012,"lang":"en","type":"article","venue":"Remediation Journal","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Strategic Environmental Research and Development Program; U.S. Department of Defense","keywords":"Environmental science; Sampling (signal processing); Aquifer; Groundwater; Water well; Hydrology (agriculture); Soil science; Temperature gradient; Atmospheric sciences; Geology; Meteorology; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004784085,0.00005881649,0.00008009449,0.0000183032,0.0001567958,0.00001539941,0.0001090599,0.00002946856,0.000105724],"category_scores_gemma":[0.0002091155,0.00003648889,0.00004293286,0.00009207371,0.00009384736,0.0002101028,0.00003557123,0.0001315486,0.00007890406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006087813,"about_ca_system_score_gemma":0.000008420381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003157307,"about_ca_topic_score_gemma":0.000001560751,"domain_scores_codex":[0.999038,0.00005528659,0.0002268909,0.00005514981,0.0004610081,0.0001637132],"domain_scores_gemma":[0.9995652,0.0001284718,0.0001017209,0.0000724535,0.00005310068,0.00007907618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005825546,0.0001237169,0.9017239,0.000006753679,0.00003185361,5.116654e-7,0.001169969,0.0010731,0.08522432,0.0003107299,0.00177863,0.008498286],"study_design_scores_gemma":[0.0001906648,0.00005109327,0.9849086,0.00001862156,0.000009093284,0.000006251307,0.00007999311,0.00004548802,0.005888954,0.00004193448,0.008713897,0.00004540315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989978,0.00007161353,0.0001477111,0.0002497585,0.0003006812,0.00004386113,0.000001698851,0.00000266813,0.0001842293],"genre_scores_gemma":[0.9994321,0.00006714671,0.0000966629,0.00008478914,0.0001260982,0.000001719808,9.500016e-7,0.000003266158,0.0001872883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08318473,"threshold_uncertainty_score":0.1487974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01090874645917794,"score_gpt":0.2368321926925404,"score_spread":0.2259234462333624,"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."}}