{"id":"W2135637880","doi":"10.1093/neuonc/not052","title":"Enhancing drug delivery for boron neutron capture therapy of brain tumors with focused ultrasound","year":2013,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Boron Compounds in Chemistry","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto; Ontario Institute for Cancer Research","funders":"National Institute of Biomedical Imaging and Bioengineering; Health Canada; National Institutes of Health","keywords":"Microbubbles; Gliosarcoma; Ultrasound; Collateral damage; Neutron capture; Focused ultrasound; Drug delivery; Brain tumor; Medicine; Chemistry; Nuclear medicine; Glioma; Boron; Cancer research; Pathology; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002171846,0.0002607239,0.0006099558,0.0000657589,0.00006690936,0.00001321064,0.0002060019,0.0002208972,0.0002120689],"category_scores_gemma":[0.0002301073,0.0002098018,0.0001188672,0.000129897,0.0002171545,0.0001003388,0.00003359936,0.0004400774,0.00001123913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002198849,"about_ca_system_score_gemma":0.0005368598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00026114,"about_ca_topic_score_gemma":0.0001894254,"domain_scores_codex":[0.9983593,0.00009212778,0.0004118869,0.0004428042,0.000224779,0.0004691018],"domain_scores_gemma":[0.9967675,0.002042352,0.0002702067,0.0004812345,0.000263451,0.0001752611],"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":[0.0007392658,0.0002333495,0.002483002,0.0001118481,0.00005863624,0.00003431195,0.0006932402,0.00000712209,0.9772683,0.00001618955,0.01412022,0.004234541],"study_design_scores_gemma":[0.005864105,0.002299725,0.004032962,0.00007773804,0.00005472659,0.0003916383,0.0005882776,0.0000514951,0.9522194,0.0001377989,0.03405711,0.0002250355],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897041,0.0003138683,0.0001396709,0.006411844,0.0002338666,0.001088498,0.00001120891,0.00008879785,0.002008086],"genre_scores_gemma":[0.9906459,0.00006660281,0.004289448,0.00415463,0.0003315643,0.0002007969,0.00002802075,0.00007391647,0.0002091254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02504889,"threshold_uncertainty_score":0.855547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411929972501961,"score_gpt":0.2718150870366111,"score_spread":0.2576957873115915,"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."}}