{"id":"W4385457521","doi":"10.1186/s12951-023-02026-7","title":"Effective treatment of metastatic sentinel lymph nodes by dual-targeting melittin nanoparticles","year":2023,"lang":"en","type":"article","venue":"Journal of Nanobiotechnology","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"Higher Education Discipline Innovation Project; Wuhan National Laboratory for Optoelectronics; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Metastasis; Melittin; Breast cancer; Metastatic breast cancer; Medicine; Primary tumor; Cancer research; Sentinel lymph node; Lymph; Cancer; Chemistry; Internal medicine; Pathology; Peptide; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009337733,0.0003895088,0.0002503514,0.0001494446,0.0001137582,0.0001513676,0.0001869525,0.0003822972,0.0004131534],"category_scores_gemma":[0.00008596072,0.0001399337,0.000280359,0.00007527326,0.0001338734,0.0002556325,0.0002370383,0.0003301017,0.0001381123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002486591,"about_ca_system_score_gemma":0.0001662385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004148512,"about_ca_topic_score_gemma":0.0008255764,"domain_scores_codex":[0.9999297,0.000009780352,0.000004921088,0.00001872637,0.00001930883,0.000017615],"domain_scores_gemma":[0.9999714,0.000004211429,0.000009232602,0.000001910936,0.000006016173,0.00000731643],"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":[0.00004734769,0.00002261928,0.00008585676,0.00008917259,0.000005722389,0.00005963157,0.00001093337,0.0002550787,0.9952041,0.0001165126,0.0001436591,0.003959429],"study_design_scores_gemma":[0.00002928694,0.0003220735,0.0004406411,0.000006998044,0.00002126342,0.000251293,0.00001227134,0.005373478,0.9903942,0.00007142015,0.003069761,0.000007402532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9401303,0.009603072,0.04552671,0.0005899444,0.0001884072,0.0001243749,0.0001905112,0.0003491325,0.003297622],"genre_scores_gemma":[0.9814634,0.002889829,0.01238399,0.0001890599,0.00003267498,0.0001180194,0.0001154665,0.00002814214,0.002779398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004148512,"threshold_uncertainty_score":0.001804113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008328258012822182,"score_gpt":0.2332891633843761,"score_spread":0.2249609053715539,"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."}}