{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002763425,0.0001685842,0.0003371009,0.0001283258,0.0001062074,0.00006255478,0.0001564351,0.0000963825,0.00002830837],"category_scores_gemma":[0.000325714,0.0001268385,0.00006538078,0.0006101123,0.0001222285,0.0001834394,0.00008349508,0.0002752024,0.000001570988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005154985,"about_ca_system_score_gemma":0.00001168207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000194458,"about_ca_topic_score_gemma":0.00004266258,"domain_scores_codex":[0.9988673,0.0001057236,0.0004709741,0.0001873815,0.0001368727,0.0002317917],"domain_scores_gemma":[0.998777,0.0005101759,0.0001228771,0.0001354179,0.0002324433,0.000222055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001693364,0.0001078147,0.5980881,0.0001386397,0.0001401616,0.00001004712,0.001065373,0.0004567326,0.3819036,0.0002917059,0.000205096,0.01742344],"study_design_scores_gemma":[0.0003976566,0.0008195908,0.9912561,0.00005912884,0.00006559193,0.00006574234,0.00009957962,0.001202057,0.001187953,0.0004075115,0.004262875,0.0001762307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946654,0.00009353664,0.002172962,0.00269418,0.00007140949,0.000239906,0.00001613172,0.00001842531,0.00002803196],"genre_scores_gemma":[0.9833211,0.00004977789,0.01602208,0.0004258981,0.0001345575,0.00001284851,0.00001219227,0.00001571719,0.000005806216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.393168,"threshold_uncertainty_score":0.5172324,"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."}}