{"id":"W2170510118","doi":"10.1109/tvlsi.2008.2000725","title":"Energy Budget Approximations for Battery-Powered Systems With a Fixed Schedule of Active Intervals","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Battery (electricity); Schedule; Computer science; Voltage; Energy (signal processing); Interval (graph theory); Energy consumption; Energy budget; Work (physics); Mathematical optimization; Electrical engineering; Control theory (sociology); Reliability engineering; Engineering; Power (physics); Mathematics; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.0001898491,0.0004089238,0.0006353601,0.0006713748,0.0002919068,0.00006743379,0.0003792461,0.0003172079,0.00003720481],"category_scores_gemma":[0.00002110535,0.0003577406,0.0001998155,0.0006966063,0.0001685431,0.0006581017,0.000003844985,0.000443821,0.00002285201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004111752,"about_ca_system_score_gemma":0.00007399108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007631037,"about_ca_topic_score_gemma":0.0002185875,"domain_scores_codex":[0.9976015,0.0001216873,0.000777632,0.000454019,0.0005047529,0.0005404165],"domain_scores_gemma":[0.9982334,0.0002969409,0.0001811625,0.0006915088,0.0004831927,0.0001138103],"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":[0.0008161074,0.001137682,0.00007082309,0.001447091,0.001071648,0.00001998676,0.002441909,0.8800786,0.09969904,0.0009174313,0.003506989,0.008792762],"study_design_scores_gemma":[0.001939958,0.0006611149,0.00003587677,0.0007393245,0.00005890766,0.0001352143,0.005588432,0.6068446,0.3800387,0.00002850092,0.003318395,0.0006109184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05749887,0.0001534421,0.9378532,0.00004974873,0.001097805,0.001197727,0.001044975,0.0006874963,0.0004168054],"genre_scores_gemma":[0.9937238,0.00008671131,0.002456302,0.00001458521,0.00006353103,0.002145265,0.00007847446,0.0001024111,0.001328937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9362249,"threshold_uncertainty_score":0.9998875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01781661929764944,"score_gpt":0.2442648485329773,"score_spread":0.2264482292353278,"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."}}