{"id":"W4408100587","doi":"10.1109/tia.2025.3546906","title":"A Novel Probabilistic Safety Risk Assessment Approach Near Transmission Line Structures Under Fault Conditions","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Saskatchewan","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; Reliability engineering; Transmission line; Electric power transmission; Computer science; Fault (geology); Probabilistic risk assessment; Risk assessment; Risk analysis (engineering); Engineering; Electrical engineering; Computer security; Artificial intelligence; Business; Telecommunications; Geology","routes":{"ca_aff":true,"ca_fund":true,"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","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001006377,0.0003546764,0.0004884089,0.000562771,0.002489561,0.0003637628,0.0009017501,0.000671395,0.0009997379],"category_scores_gemma":[0.00005152352,0.0002890414,0.000425497,0.003710803,0.0004371034,0.0002908841,0.000005973015,0.001913635,0.00008345173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002391827,"about_ca_system_score_gemma":0.0006049715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001624484,"about_ca_topic_score_gemma":0.00006586271,"domain_scores_codex":[0.9960451,0.0002926166,0.001192541,0.001047806,0.0010427,0.0003793098],"domain_scores_gemma":[0.9962542,0.001272466,0.0003161601,0.001427227,0.0004631144,0.0002667998],"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":[0.00004484838,0.001012834,0.00004354744,0.00001092735,0.0001874465,2.893558e-7,0.0001339066,0.8960615,0.0007033457,0.0129221,0.0007584009,0.08812082],"study_design_scores_gemma":[0.003128119,0.0001859891,0.0185412,0.00008895367,0.00169798,0.00003278471,0.003749077,0.5704418,0.002968607,0.3194371,0.07851645,0.001211911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002467644,0.00003006822,0.9828644,0.00523894,0.000153351,0.001142238,0.001110054,0.0001651471,0.006828151],"genre_scores_gemma":[0.9565267,0.0001105278,0.03673974,0.0004007507,0.00006259347,0.001110824,0.00008502805,0.00002466205,0.004939193],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.954059,"threshold_uncertainty_score":0.9999562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05595767451864438,"score_gpt":0.3849030351589652,"score_spread":0.3289453606403209,"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."}}