{"id":"W2907589746","doi":"10.3166/ejee.20.23-34","title":"Utilizing 2-D electrical resistivity imaging (ERI) to investigate groundwater potential","year":2018,"lang":"en","type":"article","venue":"European Journal of Electrical Engineering","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Electrical resistivity and conductivity; Groundwater; Electrical resistivity tomography; Environmental science; Remote sensing; Materials science; Geology; Electrical engineering; Geotechnical engineering; Engineering","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":[0.0001701512,0.0004330918,0.0002452535,0.0006610051,0.0001261528,0.0005321195,0.0002723002,0.0005219354,0.000599751],"category_scores_gemma":[0.0006264858,0.0002333033,0.0001525237,0.0007144398,0.0001906046,0.0009630041,0.0003565657,0.0002842476,0.0002188086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008144473,"about_ca_system_score_gemma":0.0001850953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004442923,"about_ca_topic_score_gemma":0.001530278,"domain_scores_codex":[0.9999099,0.00001594374,0.000006033972,0.0000238049,0.00003274283,0.00001145224],"domain_scores_gemma":[0.9997974,0.00007295319,0.00003989519,0.00002769992,0.00005053923,0.00001147403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001450042,0.0001098177,0.01796894,0.0003266959,0.00006147216,0.0005737225,0.0002488604,0.01613284,0.8398517,0.001370657,0.001382013,0.1218284],"study_design_scores_gemma":[0.00007986218,0.0003934031,0.04994979,0.00006798894,0.0001727643,0.002839207,0.0006063581,0.5286882,0.4015426,0.005157589,0.01033529,0.0001669979],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4675834,0.0006846707,0.5196116,0.0005354328,0.00008021985,0.0001036283,0.000953672,0.001645372,0.008802071],"genre_scores_gemma":[0.8356025,0.0004889204,0.1622912,0.000150847,0.00003246243,0.00004566857,0.0003137368,0.00005558672,0.001019109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006610051,"threshold_uncertainty_score":0.002006352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01233867338252139,"score_gpt":0.211149843292107,"score_spread":0.1988111699095856,"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."}}