{"id":"W2529405934","doi":"10.1111/gwat.12459","title":"Using Diurnal Temperature Signals to Infer Vertical Groundwater‐Surface Water Exchange","year":2016,"lang":"en","type":"review","venue":"Ground Water","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"U.S. Geological Survey; Office of Research and Development; U.S. Environmental Protection Agency","keywords":"TRACER; Tracing; Thermal diffusivity; Flux (metallurgy); Heat flux; Environmental science; Groundwater; Hydrogeology; Meteorology; Computer science; Geology; Heat transfer; Mechanics; Materials science; Geotechnical engineering; Thermodynamics","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":[0.001033065,0.001143662,0.001578483,0.004561735,0.0002375175,0.001076339,0.0009427943,0.000979374,0.001869074],"category_scores_gemma":[0.001360356,0.0004972561,0.0009719862,0.004791771,0.0004911862,0.001588029,0.0006747452,0.0008734775,0.00109204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006354204,"about_ca_system_score_gemma":0.001103466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002590918,"about_ca_topic_score_gemma":0.00398268,"domain_scores_codex":[0.9995947,0.00005854598,0.00005244506,0.0001172578,0.0001504263,0.00002662022],"domain_scores_gemma":[0.9993529,0.0003142503,0.0001152579,0.00003165436,0.0001702938,0.0000157928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000460422,0.00004434161,0.000976625,0.02980442,0.000229892,0.00009975227,0.00009112105,0.001372777,0.005732472,0.00433233,0.005564393,0.9517059],"study_design_scores_gemma":[0.00002036453,0.0002477895,0.008415104,0.008991583,0.0007692067,0.001080317,0.0002729173,0.001266687,0.01101998,0.005443868,0.9623311,0.0001411561],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006696764,0.995928,0.001456672,0.0001622684,0.0001247978,0.00001270821,0.0001227379,0.00002301117,0.001500099],"genre_scores_gemma":[0.003779845,0.9942638,0.001203572,0.00006700274,0.00006077916,0.00001698634,0.0001059208,0.000005409738,0.0004966916],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004561735,"threshold_uncertainty_score":0.006252706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05264749352395401,"score_gpt":0.2999484999112459,"score_spread":0.2473010063872919,"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."}}