{"id":"W4416579088","doi":"10.3390/nano15231761","title":"Applications of Nanomaterials in Biomedical Imaging and Cancer Therapy: 3rd Edition","year":2025,"lang":"en","type":"editorial","venue":"Nanomaterials","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Cancer; Transformative learning; Cancer imaging; Nanomaterials; Nanomedicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004225981,0.0004323809,0.00096489,0.0004934803,0.00004449305,0.00009529209,0.0003291975,0.0007233658,0.0002331215],"category_scores_gemma":[0.0000905799,0.0004229155,0.00007162951,0.0003156926,0.0001358269,0.0001709928,0.000080978,0.0001698629,0.000006201758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002657771,"about_ca_system_score_gemma":0.0003160216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001602254,"about_ca_topic_score_gemma":0.00001653715,"domain_scores_codex":[0.997775,0.00004630676,0.001003531,0.000386368,0.0004068925,0.0003819483],"domain_scores_gemma":[0.9988418,0.0003468983,0.0002357934,0.0003784499,0.0001241256,0.00007293125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006778701,0.00004073657,0.00002494328,0.001515932,0.0001041277,0.000005510435,0.0001162498,0.00001004097,0.6144694,0.00002757119,0.366299,0.01731871],"study_design_scores_gemma":[0.001100912,0.00002531989,0.00001924213,0.0006075492,0.00005009968,0.000001316978,0.00001068351,0.00002831385,0.1640099,0.0004654856,0.8333129,0.0003682913],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.02085846,0.01181632,0.0005753685,0.00002675686,0.9586802,0.001360942,0.006078098,0.0003347927,0.0002690595],"genre_scores_gemma":[0.0538974,0.05539436,0.0007735393,0.00003937099,0.882978,0.003318971,0.002942325,0.0003269725,0.0003290609],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.467014,"threshold_uncertainty_score":0.9998223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00441498395451674,"score_gpt":0.2498033309680091,"score_spread":0.2453883470134924,"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."}}