{"id":"W7125641710","doi":"10.1109/cascon66301.2025.00057","title":"Pattern-Driven and Stochastic Generation of Energy Time Series Via Differentiable Simulation","year":2025,"lang":"","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Atlantic Canada Opportunities Agency","keywords":"Series (stratigraphy); Energy (signal processing); Time series; Stochastic process; Differentiable function","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":[],"consensus_categories":[],"category_scores_codex":[0.0001216642,0.0002302847,0.0004084139,0.0002201788,0.0002637462,0.0002766089,0.0002450239,0.0001048318,0.0004410307],"category_scores_gemma":[0.00002389531,0.0002155145,0.0001020183,0.0005334291,0.0001023811,0.000681878,0.0004049812,0.00006599238,0.000006196268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002903186,"about_ca_system_score_gemma":0.00005040936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002248586,"about_ca_topic_score_gemma":0.0001117855,"domain_scores_codex":[0.9983421,0.00008466219,0.0005951138,0.0004950137,0.0002252915,0.0002577981],"domain_scores_gemma":[0.9989696,0.0000878591,0.000258248,0.0003881575,0.0002302993,0.00006579396],"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":[0.00001975103,0.0001048258,0.0006926464,0.00008685025,0.0002516026,0.000001136384,0.0003822141,0.6817939,0.01233559,0.01235746,0.0001606804,0.2918133],"study_design_scores_gemma":[0.0002228773,0.0001380878,0.0009239189,0.00007394706,0.0001154043,0.000001386519,0.0000162588,0.9949427,0.002622825,0.0006317708,0.0001257134,0.0001851358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0278259,0.0003130706,0.9706598,0.0002268171,0.0001747627,0.00009033196,0.000004926871,0.00002917707,0.0006752306],"genre_scores_gemma":[0.9876832,0.00002399402,0.002961313,0.0000771159,0.00008121918,0.000004156018,0.00002028151,0.000008300987,0.009140378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9676985,"threshold_uncertainty_score":0.8788425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01316770669348146,"score_gpt":0.2178888020959021,"score_spread":0.2047210954024206,"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."}}