{"id":"W1972235600","doi":"10.5194/hessd-2-917-2005","title":"Nonlinear estimation of aquifer parameters from surficial resistivity measurements","year":2005,"lang":"en","type":"preprint","venue":"","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University","keywords":"Aquifer; Electrical resistivity and conductivity; Geology; Permeability (electromagnetism); Hydraulic conductivity; Alluvium; Hydrogeology; Soil science; Aquifer test; Aquifer properties; Geotechnical engineering; Groundwater; Geomorphology; Soil water; Groundwater recharge","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002834669,0.0002320742,0.0001483103,0.0006064932,0.00007635108,0.0003578311,0.0001658611,0.0001878451,0.0006549878],"category_scores_gemma":[0.001324284,0.000103358,0.000126489,0.0005919678,0.0001552502,0.0004071003,0.0002436894,0.000216799,0.0002531098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001895147,"about_ca_system_score_gemma":0.0002129958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002118719,"about_ca_topic_score_gemma":0.003365506,"domain_scores_codex":[0.9998533,0.00003855468,0.00001025707,0.00003363582,0.00005157209,0.00001271201],"domain_scores_gemma":[0.9995692,0.0001633928,0.00009672738,0.00005755654,0.0001014356,0.00001164844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003361964,0.0001199732,0.3232622,0.0003767306,0.00009075506,0.0003045867,0.0003493846,0.1784963,0.2319834,0.0008659686,0.0005247286,0.2632897],"study_design_scores_gemma":[0.00001349642,0.000158649,0.2869287,0.00003246446,0.00003763947,0.0002121703,0.0002725216,0.6519765,0.05821353,0.0009101391,0.001200783,0.00004331591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.89056,0.00009919433,0.1065369,0.00003246146,0.000006260193,0.00002097071,0.0004382929,0.0003756625,0.001930251],"genre_scores_gemma":[0.9917237,0.000048038,0.007612885,0.000002986802,0.000001809247,0.000007615401,0.0002030792,0.000009131023,0.0003908045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002118719,"threshold_uncertainty_score":0.004212737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06479844679811471,"score_gpt":0.2851196368724962,"score_spread":0.2203211900743815,"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."}}