{"id":"W1981180419","doi":"10.3791/50536","title":"One Minute, Sub-One-Watt Photothermal Tumor Ablation Using Porphysomes, Intrinsic Multifunctional Nanovesicles","year":2013,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research; University at Buffalo; Princess Margaret Hospital Foundation; State University of New York","keywords":"Photothermal therapy; Porphyrin; Ablation; Photosensitizer; Materials science; Tumor ablation; Biophysics; Irradiation; Quenching (fluorescence); Photothermal effect; Liposome; Fluorescence; Conjugated system; Biomedical engineering; Photochemistry; Nanotechnology; Chemistry; Optics; Medicine; Polymer; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001543841,0.0002537755,0.000428761,0.0002834536,0.000084536,0.00009853688,0.0001886635,0.00009393936,0.0005539644],"category_scores_gemma":[0.00002550455,0.0002565972,0.0001668925,0.0002275664,0.00004724153,0.001037606,0.00003149338,0.0002181999,0.00006982509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004538078,"about_ca_system_score_gemma":0.00007430882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004474289,"about_ca_topic_score_gemma":0.000001042431,"domain_scores_codex":[0.9980711,0.00002869463,0.0008082098,0.000141338,0.0005991317,0.000351565],"domain_scores_gemma":[0.9990056,0.00005267587,0.0003659513,0.0001668706,0.0002305207,0.0001784515],"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":[0.0001380362,0.0002109651,0.0003358418,0.00003638729,0.000315127,0.000008406707,0.0003185032,0.001648912,0.9938219,0.00002431937,0.0002620285,0.002879584],"study_design_scores_gemma":[0.003279146,0.0001502715,0.003109655,0.0001922172,0.00005837105,0.0000559908,0.0001272421,0.007455097,0.9844366,0.0003212946,0.0005003533,0.0003137854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990125,0.001383395,0.006838063,0.0000106628,0.001128832,0.0002948065,0.000007917037,0.0000708338,0.0001404707],"genre_scores_gemma":[0.9868757,0.00007723228,0.01229678,0.00009381631,0.0005079556,0.00001478192,0.000007157027,0.00009242457,0.00003420648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009385312,"threshold_uncertainty_score":0.9999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.033043878087693,"score_gpt":0.3188830019614465,"score_spread":0.2858391238737535,"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."}}