{"id":"W3206760544","doi":"10.1016/j.xcrm.2021.100404","title":"Genome profiles of pathologist-defined cell clusters by multiregional LCM and G&T-seq in one triple-negative breast cancer patient","year":2021,"lang":"en","type":"article","venue":"Cell Reports Medicine","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Science, Technology and Innovation Commission of Shenzhen Municipality; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Laser capture microdissection; Breast cancer; Triple-negative breast cancer; Biology; Metastasis; Microdissection; Pathology; Lymphatic system; Cancer; Subtyping; Cancer research; Gene; Gene expression; Medicine; Genetics","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":[0.0001498527,0.0001674741,0.0003109266,0.00004508541,0.00003063858,0.000005263953,0.00005323295,0.0001206335,0.00007994575],"category_scores_gemma":[0.0001867695,0.0001514172,0.00004466305,0.000103715,0.0002325928,0.000002519507,0.000119494,0.00009630572,4.296134e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004290441,"about_ca_system_score_gemma":0.0002219208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005387327,"about_ca_topic_score_gemma":0.0002541873,"domain_scores_codex":[0.9986403,0.0000407411,0.000494971,0.0004504666,0.000167928,0.0002056051],"domain_scores_gemma":[0.9990153,0.00004642455,0.0003348367,0.0003131384,0.0001769497,0.0001133756],"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":[0.0001277582,0.0003341823,0.01592557,0.0001224899,0.00002329001,0.0001894227,0.0004541636,0.0001114861,0.9774976,0.00000182471,0.003972034,0.001240177],"study_design_scores_gemma":[0.006310705,0.001292227,0.1143599,0.0003244659,0.0001913109,0.0006199387,0.001671559,0.00006798797,0.8346653,0.0002213093,0.03944586,0.0008293914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861189,0.01158307,0.0001119932,0.0007139887,0.0002473849,0.000285371,0.000194895,0.000004042237,0.0007403131],"genre_scores_gemma":[0.9923472,0.005112746,0.0004561867,0.0003867057,0.0001279813,0.00004574817,0.0005630464,0.00002047038,0.0009398961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1428323,"threshold_uncertainty_score":0.6174614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131292628525769,"score_gpt":0.2381000639688572,"score_spread":0.2249708011162803,"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."}}