{"id":"W2136337147","doi":"10.1002/adfm.201402631","title":"Laser‐Activatible PLGA Microparticles for Image‐Guided Cancer Therapy In Vivo","year":2014,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ontario Ministry of Research and Innovation; China Medical University; Chongqing Medical University; Chongqing University","keywords":"PLGA; Materials science; In vivo; Biomedical engineering; Vaporization; Nanoparticle; Nanomedicine; Particle (ecology); Cancer cell; Laser; Biophysics; Nanotechnology; Lymph; Cancer; Pathology; Optics; Chemistry; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002222932,0.0003760488,0.000174305,0.000251672,0.000135193,0.0002278368,0.000188065,0.0004101912,0.0007373418],"category_scores_gemma":[0.0001271847,0.0001838324,0.0001563752,0.00007609457,0.0001902683,0.0002219067,0.0001193069,0.0003641809,0.0002423752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003404232,"about_ca_system_score_gemma":0.0002416354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007538746,"about_ca_topic_score_gemma":0.0007024857,"domain_scores_codex":[0.9999459,0.00001013372,0.000003403155,0.00001322569,0.00001380476,0.00001344462],"domain_scores_gemma":[0.9999477,0.00001648925,0.00001404104,0.000005418336,0.000005751464,0.00001061676],"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":[0.00007059815,0.0000385871,0.00002250006,0.00003171528,0.000002317751,0.00002235249,0.000009941405,0.0001428759,0.9973689,0.0000662523,0.00004247861,0.002181455],"study_design_scores_gemma":[0.00002582672,0.0004258218,0.0003446479,0.000004458609,0.00001328936,0.00009330248,0.000004107886,0.001545049,0.9962128,0.00002833647,0.00129884,0.000003480796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9532762,0.006163979,0.03753998,0.0003348824,0.0001035358,0.0002224917,0.000203313,0.0004422228,0.001713473],"genre_scores_gemma":[0.9780591,0.001832346,0.01621713,0.00008356316,0.00003079149,0.000151572,0.0001449695,0.00004956254,0.003431109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007538746,"threshold_uncertainty_score":0.002469897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669391438644091,"score_gpt":0.2480824012301961,"score_spread":0.2313884868437552,"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."}}