{"id":"W4417524725","doi":"10.1007/s10040-025-02989-x","title":"A 3D numerical model using a high-resolution digital elevation model to assess the cumulative effects of aquifer and river interaction","year":2025,"lang":"en","type":"article","venue":"Hydrogeology Journal","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of British Columbia; University of Northern British Columbia","funders":"","keywords":"Aquifer; Hydrogeology; Digital elevation model; Groundwater; Hydrology (agriculture); Precipitation; Elevation (ballistics); Calibration","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001369672,0.00008342791,0.0001242915,0.00006238127,0.0002006041,0.00002611171,0.00007397706,0.00004279377,0.00001053368],"category_scores_gemma":[0.00005791086,0.00005931108,0.00003057071,0.0001255042,0.0001435207,0.0003703489,0.0001566934,0.0001345429,0.00000585451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001255835,"about_ca_system_score_gemma":0.00001320197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005060343,"about_ca_topic_score_gemma":0.000008691319,"domain_scores_codex":[0.9993514,0.00006329334,0.0001836776,0.0001303947,0.0001385736,0.0001326607],"domain_scores_gemma":[0.999683,0.00009555492,0.00009473,0.00006502031,0.00002965268,0.00003199944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008892539,0.0000785381,0.03922255,0.000007910302,0.00007815199,0.000003639992,0.002054256,0.9318278,0.009992298,0.0006983994,0.0001792199,0.0157683],"study_design_scores_gemma":[0.0003019388,0.00004733177,0.03093135,0.00002100811,0.00004114908,0.00003048198,0.00006401595,0.9638165,0.0007518745,0.003891051,0.00004553657,0.00005782197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5310724,0.00001584217,0.4685207,0.000196217,0.00005243209,0.00006450716,6.290032e-7,0.000003348427,0.00007382892],"genre_scores_gemma":[0.997242,0.000006037736,0.002175272,0.0002281996,0.00001279281,0.000007515347,0.000001019164,0.000003397707,0.0003237037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4663455,"threshold_uncertainty_score":0.2418636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02355957753520053,"score_gpt":0.2789073779171063,"score_spread":0.2553478003819058,"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."}}