{"id":"W3049606037","doi":"10.1371/journal.pone.0237372","title":"Optimization of microbubble enhancement of hyperthermia for cancer therapy in an in vivo breast tumour model","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Institutes of Health","keywords":"Microbubbles; Hyperthermia; Ultrasound; In vivo; Medicine; Breast cancer; Hyperthermia therapy; Hyperthermia Treatment; Cancer; Nuclear medicine; Pathology; Radiology; 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":[0.00002633358,0.0000641764,0.0001603868,0.00003628751,0.000006928383,0.000003171085,0.00007855905,0.00003137373,0.00006217133],"category_scores_gemma":[0.000002296581,0.00006663716,0.00001716074,0.0001247822,0.000009366733,0.00005962534,0.000003950262,0.00003697411,4.069974e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002400355,"about_ca_system_score_gemma":0.0000194906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003996288,"about_ca_topic_score_gemma":0.00009751535,"domain_scores_codex":[0.9995784,0.000004952028,0.0001776596,0.0000905379,0.00006006248,0.0000884359],"domain_scores_gemma":[0.9998199,0.00001222869,0.00002694936,0.00007631975,0.00003977609,0.00002487768],"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":[0.00001852802,0.0002447868,0.0006692855,0.00005955679,0.00001419276,2.001718e-8,0.0005652563,0.3946981,0.6035047,0.00001493817,0.000004856731,0.0002057866],"study_design_scores_gemma":[0.0003491358,0.00002714129,0.000119784,0.00003814654,0.000006431601,4.216252e-8,0.00002620091,0.5877596,0.4116015,0.00001927545,0.00000425157,0.00004856514],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840586,0.0001884158,0.01501867,0.0001624888,0.000003135751,0.0003442744,0.000088874,0.00002112407,0.0001144547],"genre_scores_gemma":[0.9860557,0.0003668775,0.01328128,0.00004861717,0.00001899701,0.0001818997,0.0000122679,0.00002117506,0.00001320639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1930614,"threshold_uncertainty_score":0.2717384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04183710340819594,"score_gpt":0.229062754752282,"score_spread":0.1872256513440861,"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."}}