{"id":"W4307373120","doi":"10.3390/cancers14215235","title":"Geostatistical Modeling and Heterogeneity Analysis of Tumor Molecular Landscape","year":2022,"lang":"en","type":"article","venue":"Cancers","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Alberta","funders":"","keywords":"Tumor heterogeneity; Computational biology; Epigenetics; Genetic heterogeneity; Phenotype; Transcriptome; Spatial heterogeneity; Biology; Visualization; Computer science; Gene; Cancer; Bioinformatics; Data mining; Gene expression; Genetics; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005671129,0.0003800238,0.0004836803,0.0008401133,0.0003790063,0.0006681727,0.000429505,0.0005093322,0.0006239652],"category_scores_gemma":[0.001523491,0.0002776471,0.0009848953,0.0006037609,0.0005186808,0.0003812163,0.0005307773,0.0004165711,0.00008746445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006831422,"about_ca_system_score_gemma":0.0006862538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006076281,"about_ca_topic_score_gemma":0.005792665,"domain_scores_codex":[0.9998121,0.00007766874,0.000009166031,0.00003993837,0.00004213435,0.00001894013],"domain_scores_gemma":[0.9993073,0.0005002405,0.00007661398,0.00004446289,0.00004381946,0.00002760906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002545045,0.00001080616,0.002388917,0.00002586115,0.00004097422,0.0000490654,0.0000430776,0.9788588,0.005242054,0.00900094,0.0002226046,0.004091344],"study_design_scores_gemma":[0.000001902158,0.000004519516,0.0003458325,6.893841e-7,0.000002621579,0.000008937826,0.000008058221,0.9959441,0.0005193325,0.003025688,0.000135298,0.000002963479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2185362,0.0001475679,0.7786819,0.0003027933,0.00001384726,0.0000392312,0.0006272414,0.0006304619,0.001020768],"genre_scores_gemma":[0.9059347,0.0001547392,0.09216699,0.00005846587,0.00001857022,0.0001475595,0.000523981,0.0001301144,0.0008649036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006076281,"threshold_uncertainty_score":0.0120818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287730311445116,"score_gpt":0.2443846608595486,"score_spread":0.2315073577450975,"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."}}