{"id":"W4362670298","doi":"10.54097/hset.v40i.6589","title":"Nanotechnology in Cancer Diagnostics and Therapeutics","year":2023,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Nanotechnology; Cancer; Applications of nanotechnology; Nanomedicine; Cancer therapy; Nanoparticle; Medicine; Risk analysis (engineering); Computer science; Materials science; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0002055718,0.0001145914,0.0001367866,0.0009072241,0.00005738089,0.0000133558,0.0001649486,0.0002282112,9.179865e-8],"category_scores_gemma":[0.000121494,0.00009934261,0.000009042178,0.00178224,0.000535018,0.00000609819,0.0001877561,0.000131316,0.000001336271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001956046,"about_ca_system_score_gemma":0.00002883127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001213815,"about_ca_topic_score_gemma":0.00007885386,"domain_scores_codex":[0.9990918,0.000005282348,0.0001386155,0.0003766973,0.00007255754,0.0003150516],"domain_scores_gemma":[0.9996969,0.00001815966,0.00002557204,0.0002010648,0.00003149977,0.00002679818],"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":[0.000003526925,0.0000160231,0.01071554,0.000008117257,0.000005546166,0.0000203091,0.0000245885,0.0001084948,0.9719806,0.007660398,0.00002452782,0.009432316],"study_design_scores_gemma":[0.0002801442,0.0001397766,0.007454606,0.00006250093,0.000007032733,0.00002936632,0.00008772106,0.004498546,0.9632972,0.00121002,0.02264711,0.0002860087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961845,0.001048377,0.0001123338,0.002341274,0.00006766147,0.00006899112,0.000003064457,0.0001595862,0.00001420634],"genre_scores_gemma":[0.9835958,0.01472928,0.001564445,0.00003230574,0.00001816258,0.00002165503,0.000002019332,0.0000090781,0.00002726456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02262258,"threshold_uncertainty_score":0.4051074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008445271023247283,"score_gpt":0.2688118926949219,"score_spread":0.2603666216716746,"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."}}