{"id":"W2130849876","doi":"10.1038/modpathol.3800491","title":"TMA-Combiner, a simple software tool to permit analysis of replicate cores on tissue microarrays","year":2005,"lang":"en","type":"article","venue":"Modern Pathology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"Michael Smith Health Research BC; National Science Foundation","keywords":"Tissue microarray; Replicate; DNA microarray; Microarray; Computer science; Software; Computational biology; Microarray analysis techniques; Epitope; Bioinformatics; Pathology; Biology; Antibody; Immunohistochemistry; Medicine; Mathematics; Immunology; Genetics; Programming language","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":[0.0001112854,0.0001374083,0.0002429719,0.0001733128,0.00004727201,0.000007914944,0.0002189466,0.0001584325,0.00007569114],"category_scores_gemma":[0.00008146434,0.0001296377,0.0001134016,0.000222,0.00004543077,0.000002195905,0.00008377113,0.00006133335,0.00002821114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001342271,"about_ca_system_score_gemma":0.00003023208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007763913,"about_ca_topic_score_gemma":0.00004707207,"domain_scores_codex":[0.9988539,0.00005912399,0.000256482,0.0005295015,0.00009948394,0.0002015345],"domain_scores_gemma":[0.99894,0.000009381262,0.0001081265,0.0007870737,0.00008770958,0.00006769221],"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":[0.0001111742,0.00009626866,0.001981813,0.000004287191,0.00007182257,0.000002357986,0.0001425384,0.003386933,0.9498283,0.00007759661,0.004696744,0.03960011],"study_design_scores_gemma":[0.0004297183,0.0003906075,0.02284695,0.000004548583,0.0001353057,0.000007570863,0.0000239051,0.0006719567,0.8458825,0.0001138786,0.1292613,0.0002317002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488289,0.0002571987,0.04971506,0.000521119,0.00004642573,0.000158928,0.00006704497,0.00002016453,0.0003851927],"genre_scores_gemma":[0.9938321,0.0000466189,0.002785551,0.001435377,0.00007710417,0.00006778771,0.0002697498,0.00001922837,0.001466559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1245646,"threshold_uncertainty_score":0.5286472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01469887208309625,"score_gpt":0.2878245905353845,"score_spread":0.2731257184522883,"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."}}