{"id":"W4403390731","doi":"10.1109/itherm55375.2024.10709478","title":"Accelerating Thermal Analysis of Chiplet Designs by Embedding FANTASTIC BCI-ROMs in CFD models","year":2024,"lang":"en","type":"article","venue":"","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Siemens (Canada)","funders":"","keywords":"Computational fluid dynamics; Computer science; Embedding; Brain–computer interface; Artificial intelligence; Engineering; Aerospace engineering","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":[0.0003590206,0.0005519705,0.0004299269,0.000269585,0.0003012955,0.0008272246,0.0008536702,0.0007083356,0.004158982],"category_scores_gemma":[0.00117789,0.0004440171,0.000617589,0.000212971,0.0004761856,0.0007391118,0.0005002064,0.001019368,0.001060927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000717395,"about_ca_system_score_gemma":0.001097423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00316959,"about_ca_topic_score_gemma":0.003784172,"domain_scores_codex":[0.9998174,0.0000294437,0.000006223635,0.000020001,0.0001062373,0.00002081104],"domain_scores_gemma":[0.9995735,0.0001715158,0.00004077963,0.0001110366,0.00008407303,0.00001909603],"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":[0.00001741022,0.00002028778,0.0003633545,0.00006321081,0.000007886448,0.00004553043,0.00004737541,0.9735463,0.01097917,0.007237264,0.0005874382,0.007084952],"study_design_scores_gemma":[0.000004604874,0.00001744274,0.0001083452,0.000008438007,0.000003099909,0.00001770838,0.000009457107,0.991028,0.005116637,0.001292962,0.002386592,0.000006721799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06497972,0.0001282652,0.907338,0.0002340186,0.00007716701,0.0001593059,0.0004774549,0.001612674,0.02499339],"genre_scores_gemma":[0.5926612,0.0004100443,0.3938593,0.0001202637,0.00002661187,0.0003688699,0.0005973843,0.0006532414,0.01130316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004158982,"threshold_uncertainty_score":0.01391315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180345440821881,"score_gpt":0.2590177176436424,"score_spread":0.2272142632354236,"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."}}