{"id":"W2803299750","doi":"10.1039/c8lc00184g","title":"Isolation and genome sequencing of individual circulating tumor cells using hydrogel encapsulation and laser capture microdissection","year":2018,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Prostate Cancer Canada","keywords":"Laser capture microdissection; Encapsulation (networking); Isolation (microbiology); Microdissection; Genome; Nanotechnology; Computational biology; Chemistry; Biology; Molecular biology; Materials science; Genetics; Gene; Bioinformatics; Computer science; Gene expression","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":[0.000106834,0.0000840364,0.00007949633,0.00003830575,0.00007612906,0.00002309924,0.00003074828,0.00006967515,0.00000466833],"category_scores_gemma":[0.00003154949,0.00008885383,0.00001756844,0.0000489547,0.000050353,0.000004372318,0.00004105187,0.00004376284,4.417506e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001955425,"about_ca_system_score_gemma":0.00003584684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006924256,"about_ca_topic_score_gemma":0.00004897094,"domain_scores_codex":[0.9995003,0.00001554261,0.0001293822,0.0001974831,0.00005990091,0.0000973987],"domain_scores_gemma":[0.9997064,0.00001155901,0.00009994359,0.0001003347,0.00004629745,0.00003547999],"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":[0.00002371441,0.000007459249,0.002404452,0.00001729706,0.00001267026,6.421479e-7,0.000394385,0.0004367513,0.9964571,0.00003791241,0.000004766507,0.0002028213],"study_design_scores_gemma":[0.0004841738,0.0002373213,0.02185145,0.00003483724,0.00003902043,0.00003392992,0.000199329,0.00471136,0.9718542,0.0001994827,0.0001793404,0.0001755735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987219,0.0002326444,0.0006650966,0.000009700343,0.00007796568,0.0001009858,0.00004533999,0.000003894415,0.0001424723],"genre_scores_gemma":[0.9982274,0.00002269737,0.001288584,0.0001527717,0.0002267857,0.00000143054,0.00005925584,0.00001225643,0.00000877182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02460295,"threshold_uncertainty_score":0.3623354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343431371377834,"score_gpt":0.2323146683824272,"score_spread":0.2188803546686488,"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."}}