{"id":"W2076976730","doi":"10.1111/j.1365-2184.2009.00619.x","title":"Characterization of brain cancer stem cells: a mathematical approach","year":2009,"lang":"en","type":"article","venue":"Cell Proliferation","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fields Institute for Research in Mathematical Sciences; McMaster University; University of Waterloo","funders":"National Cancer Institute; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Brain cancer; Stem cell; Neuroscience; Cancer stem cell; Hierarchy; Cancer research; Medicine; Biology; Cancer; Computational biology; Cell biology; Internal medicine; Political science","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":[0.0004895686,0.0001963224,0.0003924481,0.00009140535,0.00006134442,0.00002824809,0.0001716668,0.0001644205,0.0001677878],"category_scores_gemma":[0.00007457887,0.0001612695,0.00008110349,0.0001951516,0.0000676867,0.0001437007,0.00002343688,0.0001461556,0.00002661246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004231124,"about_ca_system_score_gemma":0.00004774923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.691719e-7,"about_ca_topic_score_gemma":3.17398e-7,"domain_scores_codex":[0.9984776,0.0001375903,0.0006129695,0.000274687,0.0002635284,0.0002336284],"domain_scores_gemma":[0.9990086,0.000156982,0.0003120193,0.0003258591,0.0001191451,0.00007736892],"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":[0.00004154811,0.0008811904,0.00006810835,0.0008682861,0.00001641669,0.000001282037,0.00150822,0.000004087639,0.8106933,0.1832322,0.0007974337,0.001887946],"study_design_scores_gemma":[0.0005322169,0.0001763892,0.000133166,0.00007981767,0.00005778718,0.000008041262,0.00006937054,0.01347816,0.8261717,0.1589553,0.0000862771,0.0002517362],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.801229,0.00002012223,0.1878102,0.0007558514,0.00007569068,0.001075888,0.00001848815,0.0001438012,0.008870913],"genre_scores_gemma":[0.9856393,0.000007096152,0.0115774,0.0002761962,0.0001161348,0.00009263817,0.00002874083,0.00002391563,0.002238544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1844103,"threshold_uncertainty_score":0.6576378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03372389411146823,"score_gpt":0.2771332239571272,"score_spread":0.243409329845659,"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."}}