{"id":"W3021874351","doi":"10.5539/jgg.v12n1p25","title":"Use of Ground Penetrating Radar, Hydrogeochemical Testing, and Aquifer Characterization to Establish Shallow Groundwater Supply to the Rehabilitated Ni-les’tun Unit Floodplain: Bandon Marsh, Coquille Estuary, Oregon, USA","year":2020,"lang":"en","type":"article","venue":"Journal of Geography and Geology","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Oregon Sea Grant, Oregon State University; U.S. Fish and Wildlife Service; National Oceanic and Atmospheric Administration; U.S. Department of Commerce","keywords":"Hydrology (agriculture); Groundwater; Estuary; Aquifer; Geology; Piezometer; Marsh; Saltwater intrusion; Wetland; Environmental science; Oceanography; Geotechnical engineering; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001499585,0.0001857806,0.00008660108,0.000325215,0.0003535237,0.000512582,0.0002589979,0.0001153782,0.0005780637],"category_scores_gemma":[0.0002313456,0.000102224,0.000071736,0.0003200336,0.0002759584,0.0002419598,0.0002558605,0.0001424791,0.00008018628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006313018,"about_ca_system_score_gemma":0.0006396887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05753817,"about_ca_topic_score_gemma":0.2526382,"domain_scores_codex":[0.9999144,0.000008303035,0.000007564318,0.00002862361,0.00002719982,0.00001392151],"domain_scores_gemma":[0.9998024,0.00001887473,0.00006628632,0.00001426863,0.00006509778,0.00003307838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001207248,0.0001521134,0.9460965,0.00002101401,0.00001671435,0.0001446245,0.0004968763,0.0001977212,0.03591183,0.00003281855,0.00009114821,0.01671796],"study_design_scores_gemma":[0.000005257605,0.0001076236,0.993144,0.000005204555,0.000009673378,0.00008185981,0.0008973244,0.00106833,0.004232631,0.00001179803,0.000432755,0.000003609249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994031,0.000008582372,0.0001356333,0.000005425936,3.730078e-7,0.000008394578,0.00007034487,0.00000379617,0.0003643625],"genre_scores_gemma":[0.998251,0.00002392471,0.0008563838,0.000009139761,5.861148e-7,0.00001401077,0.0002482276,0.000001472666,0.0005952409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05753817,"threshold_uncertainty_score":0.1144065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02296016902934499,"score_gpt":0.2261568863726359,"score_spread":0.2031967173432909,"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."}}