{"id":"W2025896306","doi":"10.1190/1.3505764","title":"Using helicopter electromagnetic (HEM) surveys to identify potential hazards at coal-waste impoundments: Examples from West Virginia","year":2010,"lang":"en","type":"article","venue":"Geophysics","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Energy Technology Laboratory","keywords":"Levee; Slurry; Geology; Resistive touchscreen; Mining engineering; Electrical resistivity and conductivity; Coal; Coal mining; Geotechnical engineering; Hydrology (agriculture); Environmental science; Engineering; Waste management; Environmental engineering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001720925,0.0002983135,0.0002982684,0.00005258903,0.0001874434,0.0001379439,0.0003039915,0.0001143928,0.0002776987],"category_scores_gemma":[0.00001702509,0.0003242573,0.0001286549,0.0002383775,0.00005262433,0.0001420063,0.0001625021,0.00032262,0.0009065406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005168946,"about_ca_system_score_gemma":0.00001846164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007875242,"about_ca_topic_score_gemma":0.0002108427,"domain_scores_codex":[0.9984815,0.00006307397,0.0002914399,0.0003966177,0.0002720552,0.0004953513],"domain_scores_gemma":[0.9989418,0.00009601993,0.00005298619,0.0006128337,0.00007717084,0.0002191366],"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":[0.000003843082,0.00004471766,0.0001393942,0.00001244038,0.00003911544,0.000002683017,0.00006494771,0.0007026169,0.9915276,0.0003157725,0.00009606322,0.007050817],"study_design_scores_gemma":[0.001479756,0.0002409359,0.6530325,0.00007696538,0.0003636865,0.00001570344,0.0001187826,0.02410437,0.2848812,0.02731727,0.006183172,0.002185591],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649551,0.00003001636,0.0332833,0.00006016077,0.0007293354,0.0002709231,0.0001687762,0.0001977728,0.0003046537],"genre_scores_gemma":[0.9741288,0.000009949978,0.02466013,0.0000735026,0.0008103672,0.00005112233,0.00008304958,0.00007877574,0.0001042424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7066464,"threshold_uncertainty_score":0.999921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744548940575221,"score_gpt":0.2867843556124372,"score_spread":0.269338866206685,"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."}}