{"id":"W2781392573","doi":"10.1115/1.4038791","title":"Optimization of Electrode Configuration and Pulse Strength in Irreversible Electroporation for Large Ablation Volumes Without Thermal Damage","year":2017,"lang":"en","type":"article","venue":"Journal of Engineering and Science in Medical Diagnostics and Therapy","topic":"Microbial Inactivation Methods","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Saskatchewan","funders":"","keywords":"Ablation; Volume (thermodynamics); Electrode; Maximum temperature; Materials science; Irreversible electroporation; Analytical Chemistry (journal); Electroporation; Biomedical engineering; Composite material; Chemistry; Medicine; Chromatography; Thermodynamics; Cardiology; Physics","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":[0.0009955071,0.0000455699,0.00009144276,0.00008301212,0.00005607064,0.00003839474,0.00006636878,0.00005437765,0.000002397891],"category_scores_gemma":[0.001936967,0.00003892138,0.000008807599,0.00004617481,0.00006509297,0.00003495846,0.00001139316,0.00006855578,3.392191e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000681163,"about_ca_system_score_gemma":0.00007013692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007163057,"about_ca_topic_score_gemma":0.000007479096,"domain_scores_codex":[0.9995549,0.0000175912,0.0001650937,0.00007818814,0.0001000088,0.00008421778],"domain_scores_gemma":[0.9996107,0.00005408507,0.0001309078,0.00004988397,0.0001128166,0.00004157273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009859487,0.0000598708,0.03186516,0.00002029229,0.000007161909,0.000001262634,0.0001303426,0.007264037,0.9457632,0.0004484435,0.00001395673,0.01432767],"study_design_scores_gemma":[0.002727612,0.0008499497,0.1841088,0.0001268808,0.000007779588,0.00001328813,0.00006409148,0.4892916,0.3222407,0.0001421673,0.00028285,0.0001443197],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9305048,0.0003912144,0.06882141,0.0001642741,0.0000418602,0.00006674174,0.000001311067,5.503842e-7,0.00000783742],"genre_scores_gemma":[0.9895825,0.00478486,0.005551519,0.00002474461,0.0000452257,0.000001375706,0.000003817631,0.000003149494,0.000002797818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6235225,"threshold_uncertainty_score":0.231887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009769213307465486,"score_gpt":0.2972574280986888,"score_spread":0.2874882147912233,"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."}}