{"id":"W4415168559","doi":"10.1049/icp.2025.1491","title":"Improving LV networks hosting capacity via the use of batteries – a Monte-Carlo analysis","year":2025,"lang":"en","type":"article","venue":"IET conference proceedings.","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Iron Ore Company (Canada)","funders":"","keywords":"Overvoltage; Limiting; Grid; Energy storage; Voltage; Power (physics); Transmission (telecommunications); Inverter; Reliability (semiconductor); Battery (electricity)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001046785,0.0003622841,0.0004692982,0.0005529852,0.0003190342,0.0007666079,0.0005019145,0.0006898423,0.002083189],"category_scores_gemma":[0.002353514,0.000282386,0.0006108543,0.0004880011,0.0004069674,0.0005908644,0.0002612715,0.0004572726,0.0001788696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112062,"about_ca_system_score_gemma":0.0006797969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0107745,"about_ca_topic_score_gemma":0.009576539,"domain_scores_codex":[0.9997255,0.0001150725,0.000007674328,0.00002412633,0.00006430007,0.00006327693],"domain_scores_gemma":[0.9982654,0.001329555,0.0001169655,0.00008136608,0.0001699532,0.00003671362],"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":[0.00001342108,0.000009214318,0.0003191053,0.00001013823,0.000005121043,0.00001296379,0.000005347169,0.9974241,0.0002398581,0.000778357,0.00007985154,0.001102398],"study_design_scores_gemma":[0.00000476646,0.00002311435,0.0002400337,0.000006854401,0.000007634629,0.000008673919,0.000006964082,0.9987894,0.0003458344,0.000357774,0.0002055689,0.000003420519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8247377,0.001392746,0.1358102,0.0006299283,0.00006166046,0.0001171559,0.0004992323,0.0003374676,0.03641394],"genre_scores_gemma":[0.9901224,0.0002241441,0.008189496,0.00003272315,0.000008809314,0.00004385402,0.00009088497,0.00002555451,0.00126208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0107745,"threshold_uncertainty_score":0.02142358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02432913708665256,"score_gpt":0.1978404761635136,"score_spread":0.1735113390768611,"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."}}