{"id":"W4408429139","doi":"10.5194/egusphere-egu25-14411","title":"Field study on the application of time-lapse electrical resistivity tomography to assess the performance of an inclined multi-layer cover system reducing water infiltration","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université du Québec en Abitibi-Témiscamingue; GDG Environnement; École de Technologie Supérieure","funders":"","keywords":"Electrical resistivity and conductivity; Infiltration (HVAC); Electrical resistivity tomography; Cover (algebra); Environmental science; Field (mathematics); Tomography; Remote sensing; Soil science; Materials science; Geology; Engineering; Electrical engineering; Optics; Physics; Composite material; Mechanical engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007424234,0.0001915539,0.0003153791,0.0001032643,0.0000969668,0.00002944117,0.0004170316,0.0001304815,0.000007778876],"category_scores_gemma":[0.00005050952,0.0001034973,0.00009543426,0.0003472771,0.00001814904,0.00003889509,0.0001569656,0.0004107828,0.00001095687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003757018,"about_ca_system_score_gemma":0.00002055416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002044235,"about_ca_topic_score_gemma":0.00001021653,"domain_scores_codex":[0.9986812,0.0002085408,0.0004406318,0.0002958575,0.0002271509,0.0001466186],"domain_scores_gemma":[0.9982588,0.000535111,0.00009065647,0.0009362412,0.0001440488,0.00003517801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003016345,0.002165287,0.002358044,0.00157481,0.0005363686,3.343028e-7,0.002642712,0.3275366,0.6245076,0.005237954,0.0004562567,0.03268242],"study_design_scores_gemma":[0.0001525128,0.0002913318,0.03720547,0.0001267002,0.0001037238,1.7266e-7,0.0001577563,0.6342385,0.3274142,0.00006226923,0.00005001727,0.0001972885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.878113,0.00000367103,0.119083,0.0001190653,0.00006689743,0.001728615,0.00001834975,0.00009221224,0.0007752471],"genre_scores_gemma":[0.9944855,0.000002220082,0.00450998,0.00003505136,0.000060061,0.0007940719,0.00001691097,0.00001281877,0.00008336038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.306702,"threshold_uncertainty_score":0.4220498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03154142197095516,"score_gpt":0.3109270012517404,"score_spread":0.2793855792807852,"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."}}