{"id":"W4323667862","doi":"10.3389/fcell.2023.1065586","title":"Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity","year":2023,"lang":"en","type":"article","venue":"Frontiers in Cell and Developmental Biology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Mitacs","keywords":"Cluster analysis; Computational biology; Statistical hypothesis testing; Linear model; Set (abstract data type); Phenotype; Spatial analysis; Computer science; Biology; Data mining; Gene; Mathematics; Genetics; Statistics","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":[0.0001729292,0.0001537709,0.0003373541,0.0003198438,0.00005711639,0.00000802871,0.0001283178,0.000196797,0.000004449375],"category_scores_gemma":[0.00004016402,0.000149127,0.00008059246,0.0005068104,0.00009751781,0.000001998941,0.00006873604,0.00005527578,0.000002275725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001470446,"about_ca_system_score_gemma":0.00005339803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008290043,"about_ca_topic_score_gemma":0.000173536,"domain_scores_codex":[0.9989717,0.00002796912,0.0003065196,0.0003893511,0.00005647898,0.000247987],"domain_scores_gemma":[0.9996654,0.0000324041,0.0000686929,0.0001008406,0.00005600737,0.00007660045],"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":[0.0004973375,0.000139676,0.2040322,0.00002145907,0.0002406516,0.000001329045,0.0001387913,0.00004278407,0.7896466,0.00001766871,0.0006151933,0.00460633],"study_design_scores_gemma":[0.003303639,0.001292594,0.08847777,0.000009388837,0.0002238732,0.000002490554,0.000354109,0.003945281,0.8970595,0.0005246691,0.004198659,0.0006080141],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975637,0.0001126299,0.02329308,0.00003645395,0.0002538314,0.000354795,0.0001672538,0.00001425259,0.0001306638],"genre_scores_gemma":[0.9850556,0.0001245408,0.01245844,0.000198357,0.00003356431,0.00005747394,0.002005721,0.00001314971,0.00005319928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1155544,"threshold_uncertainty_score":0.6081223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008829922410149892,"score_gpt":0.2322094494116673,"score_spread":0.2233795270015174,"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."}}