{"id":"W4400140816","doi":"10.1093/bioinformatics/btae263","title":"Adaptive digital tissue deconvolution","year":2024,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; European Commission; Trond Mohn stiftelse; Ministère de l'Économie, de la Science et de l'Innovation - Québec; California Department of Fish and Game","keywords":"Deconvolution; Computer science; Blind deconvolution; Algorithm; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007959335,0.0007865588,0.0004817402,0.0006936124,0.0002798994,0.001101343,0.001404001,0.001001914,0.004977671],"category_scores_gemma":[0.002005559,0.0003555059,0.0008883139,0.0007641679,0.0009443491,0.001029081,0.001539676,0.001147617,0.002697097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007291632,"about_ca_system_score_gemma":0.0009825849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002315891,"about_ca_topic_score_gemma":0.001763083,"domain_scores_codex":[0.9996357,0.00006192912,0.00002217415,0.0001008703,0.0001494011,0.00002989209],"domain_scores_gemma":[0.9994509,0.0002098951,0.00005437537,0.0001178508,0.000126261,0.00004081314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003994967,0.00008867528,0.003396849,0.0008477549,0.0001349789,0.0005311692,0.0002535271,0.3148275,0.1268354,0.04872584,0.01557385,0.4883851],"study_design_scores_gemma":[0.000022143,0.00003194155,0.0005548942,0.0000387238,0.00002314245,0.0005406134,0.00002570019,0.9175096,0.04438847,0.02060544,0.01621652,0.00004292356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002386642,0.0001571171,0.9939528,0.0001387716,0.00003726142,0.00002559688,0.0002484662,0.001465865,0.001587456],"genre_scores_gemma":[0.08492012,0.0006484098,0.9068547,0.0003684698,0.00007786844,0.0001208516,0.00130095,0.0005479172,0.005160574],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004977671,"threshold_uncertainty_score":0.01665199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0130592726368092,"score_gpt":0.2318475094562834,"score_spread":0.2187882368194742,"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."}}