{"id":"W2154938422","doi":"10.1109/tbme.2009.2014243","title":"Automatically Generated, Anatomically Accurate Meshes for Cardiac Electrophysiology Problems","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Heart, Lung, and Blood Institute; Engineering and Physical Sciences Research Council","keywords":"Polygon mesh; Electrophysiology; Computer science; Cardiac electrophysiology; Neuroscience; Computer graphics (images); Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0000833553,0.0001991523,0.0002140808,0.00008056303,0.00007213786,0.00001896055,0.0001572337,0.000277353,0.000006953795],"category_scores_gemma":[0.00001861728,0.0001780756,0.0001594907,0.000150408,0.00004636577,0.000005123181,0.000001385447,0.0001694259,0.000003667665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002609078,"about_ca_system_score_gemma":0.00006431864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002211408,"about_ca_topic_score_gemma":8.770447e-7,"domain_scores_codex":[0.9989523,0.00001742787,0.0002369012,0.0003167013,0.0001184936,0.0003581218],"domain_scores_gemma":[0.9995278,0.0000180218,0.00003114307,0.0002180005,0.00005115521,0.0001539329],"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":[0.00005955582,0.00005655646,1.562672e-7,0.00002096539,0.00008071539,0.000001207482,0.000006764927,0.02324903,0.9611015,0.00013495,0.0001612426,0.01512734],"study_design_scores_gemma":[0.00124153,0.002610646,0.0001453252,0.0000476311,0.00008740493,0.00002636754,0.000005027573,0.2709055,0.7072967,0.0004596087,0.01649823,0.0006760862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1028123,0.0001390965,0.895974,0.0002754114,0.0003447639,0.0003021565,0.0000474448,0.00008718608,0.0000176858],"genre_scores_gemma":[0.9872314,0.0001412105,0.01189,0.0002870882,0.000220547,0.00008599898,0.0000664558,0.00002543166,0.00005189597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8844191,"threshold_uncertainty_score":0.7261711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004388076145710037,"score_gpt":0.2186763425944341,"score_spread":0.214288266448724,"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."}}