{"id":"W2980544438","doi":"10.1109/tbme.2019.2947292","title":"A Novel Method to Increase Tumor Ablation Zones With RFA by Injecting the Cationic Polymer Solution to Tissues: <i>In Vivo</i> and Computational Studies","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Hepatocellular Carcinoma Treatment and Prognosis","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Saskatchewan","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"In vivo; Cationic polymerization; Ablation; Polymer; Biomedical engineering; Ablation zone; Materials science; Chemistry; Radiofrequency ablation; Nuclear chemistry; Polymer chemistry; Medicine; Organic chemistry; Internal medicine; 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":[0.0002351577,0.0001419339,0.0001992209,0.0002288395,0.00007667443,0.00001449064,0.00003515703,0.00004349384,0.00002087953],"category_scores_gemma":[0.0000141563,0.000101751,0.00003080279,0.0005191918,0.00002242994,0.00006065162,0.000002058403,0.0001406089,0.00001212801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001208558,"about_ca_system_score_gemma":0.00004251029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002362141,"about_ca_topic_score_gemma":0.00002416244,"domain_scores_codex":[0.999121,0.00001984981,0.0001926259,0.0002319478,0.0002534184,0.000181132],"domain_scores_gemma":[0.9994221,0.0002563785,0.00002369169,0.00009841518,0.00004536213,0.0001541018],"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":[0.001188347,0.001600792,0.007869334,0.000705888,0.001186889,0.00006509596,0.01029914,0.1218063,0.7923869,0.0002619406,0.0005533861,0.06207598],"study_design_scores_gemma":[0.006186314,0.002788879,0.003207769,0.001331794,0.0004964004,0.0005058442,0.001130236,0.8701066,0.108575,0.0000154533,0.004883699,0.0007720417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3603171,0.0001707255,0.6371889,0.001712999,0.00007406314,0.0004682706,0.00001486667,0.00004274201,0.00001033622],"genre_scores_gemma":[0.9718183,0.00000878136,0.02749253,0.0003298607,0.00003314688,0.000135176,0.00000909441,0.0000196835,0.0001533949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7483003,"threshold_uncertainty_score":0.4149285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02327313230306394,"score_gpt":0.2660437413337866,"score_spread":0.2427706090307226,"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."}}