{"id":"W4307949351","doi":"10.3390/a15110399","title":"Design of HIFU Treatment Plans Using Thermodynamic Equilibrium Algorithm","year":2022,"lang":"en","type":"article","venue":"Algorithms","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Korea Electrotechnology Research Institute","keywords":"Thermodynamic equilibrium; Benchmark (surveying); Population; Computer science; High-intensity focused ultrasound; Thermodynamic process; Evolutionary algorithm; Mathematical optimization; Algorithm; Mathematics; Ultrasound; Material properties; Physics; Thermodynamics; Geology","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":[0.000475872,0.0007471794,0.0007694173,0.000722584,0.0004521427,0.0006743441,0.0008933133,0.001086016,0.002578933],"category_scores_gemma":[0.001091562,0.0005121297,0.0006390215,0.0003764146,0.0004451775,0.0005585417,0.0007694048,0.0005198809,0.0002851363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006532646,"about_ca_system_score_gemma":0.001144928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003132668,"about_ca_topic_score_gemma":0.002159956,"domain_scores_codex":[0.9997839,0.00005016089,0.00001163732,0.00005161112,0.000067966,0.00003469325],"domain_scores_gemma":[0.9998022,0.00008954325,0.00002803959,0.000008308953,0.00005590636,0.00001606399],"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":[0.00003487005,0.00002341442,0.0002712016,0.00003219661,0.00001380535,0.00004868446,0.000033407,0.9687716,0.002403834,0.00262638,0.0004433289,0.0252973],"study_design_scores_gemma":[0.000006423221,0.00001627773,0.00005201666,0.000002709925,0.00000324411,0.0000101434,0.000007614057,0.9986491,0.0003499895,0.0005405058,0.0003588492,0.000003265104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02205916,0.0002133775,0.9733129,0.0001094707,0.00002626615,0.0001541117,0.00003581259,0.0002749905,0.003813884],"genre_scores_gemma":[0.5437098,0.0002903373,0.4500695,0.000146933,0.00002972477,0.0009556522,0.0001719004,0.0001527031,0.004473411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003132668,"threshold_uncertainty_score":0.008627415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02618247100813301,"score_gpt":0.2339881794974253,"score_spread":0.2078057084892923,"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."}}