{"id":"W2787592863","doi":"10.1021/acsnano.7b08813","title":"<i>Ex Vivo</i> Detection of Circulating Tumor Cells from Whole Blood by Direct Nanoparticle Visualization","year":2018,"lang":"en","type":"article","venue":"ACS Nano","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; BC Cancer Agency; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Circulating tumor cell; Visualization; Nanoshell; In vivo; Cancer; Biomedical engineering; Cancer research; Materials science; Nanotechnology; Pathology; Nanoparticle; Medicine; Metastasis; Computer science; Biology; Internal 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001314787,0.0001058555,0.000231572,0.00004559041,0.00006596678,0.00001405025,0.00004831815,0.00004436604,0.0001799545],"category_scores_gemma":[0.00005259628,0.00009966407,0.00006057249,0.0002983978,0.00006024884,0.00008027236,0.00002619741,0.00004244634,0.00005309753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000314299,"about_ca_system_score_gemma":0.00003799771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007420903,"about_ca_topic_score_gemma":0.00007766688,"domain_scores_codex":[0.9990661,0.00003767545,0.0002672492,0.0002328848,0.0002137614,0.0001823858],"domain_scores_gemma":[0.9993755,0.00003928507,0.0001434961,0.0002376598,0.0001237968,0.00008021208],"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":[0.00005510819,0.0001499923,0.0009015322,0.00003074372,0.0000509841,0.000003249393,0.0002746538,0.000001736082,0.9934676,0.000003236777,0.001133408,0.003927792],"study_design_scores_gemma":[0.00111212,0.0003249969,0.0003114651,0.00006736479,0.0002496295,0.000005324338,0.00006504411,0.0001528011,0.9733897,0.0000135757,0.0242118,0.00009612575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971162,0.00047228,0.000386093,0.00003688491,0.0002888474,0.0001855573,0.00007345579,0.00005213641,0.001388529],"genre_scores_gemma":[0.998757,0.00002804972,0.0002008374,0.0002729036,0.0002374806,0.000007617382,0.00002469308,0.00002578113,0.0004456572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0230784,"threshold_uncertainty_score":0.4064183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009549758935782008,"score_gpt":0.2489814714477349,"score_spread":0.2394317125119529,"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."}}