{"id":"W1969832949","doi":"10.1109/tia.2013.2271272","title":"Time-Dependent Finite-Volume Model of Thermoelectric Devices","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"Advanced Thermoelectric Materials and Devices","field":"Materials Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Thermoelectric effect; Heat sink; Finite volume method; Thermal conduction; Thermoelectric generator; Thermoelectric cooling; Materials science; Mechanics; Mechanical engineering; Discretization; Thermoelectric materials; Partial differential equation; Finite element method; Thermodynamics; Engineering; Physics; Mathematics; Composite material; Mathematical analysis","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001439379,0.0002054207,0.0002527909,0.0001436399,0.0002541645,0.00005882568,0.0003897333,0.0002829348,0.006357865],"category_scores_gemma":[0.000003900377,0.0001871113,0.00007415764,0.0004270553,0.0001140471,0.0002970203,0.000002715627,0.0003165231,0.0022222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005246279,"about_ca_system_score_gemma":0.00009562699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008581873,"about_ca_topic_score_gemma":0.000005463515,"domain_scores_codex":[0.9985452,0.00005577435,0.0004394794,0.0003720723,0.0002718651,0.0003155521],"domain_scores_gemma":[0.9988531,0.0001398902,0.0002255123,0.0005027488,0.0001594198,0.0001192737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001679107,0.0002592354,0.000003008111,0.00002268894,0.00001508507,1.447687e-7,0.00006151572,0.1922735,0.7961056,0.0001559431,0.000114726,0.01097184],"study_design_scores_gemma":[0.0002525571,0.0001084203,0.00002655815,0.00001877987,0.00004979727,0.000004323087,0.00006113189,0.07963553,0.917121,0.002019668,0.0004170389,0.0002851982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2817004,0.00003915304,0.7144345,0.0001850591,0.00007248831,0.0007727249,0.0001515944,0.0001805279,0.002463536],"genre_scores_gemma":[0.9929777,0.00001821117,0.001868875,0.0001515041,0.00005165676,0.001317499,0.000004464165,0.00003115848,0.003578973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7125657,"threshold_uncertainty_score":0.9985547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536219140123344,"score_gpt":0.2403843853401575,"score_spread":0.2250221939389241,"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."}}