{"id":"W4401975412","doi":"10.7554/elife.98469","title":"Artificial intelligence driven tumor risk stratification from single-cell transcriptomics using phenotype algebra","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Science and Engineering Research Board","keywords":"Phenotype; Grading (engineering); Computer science; Algebra over a field; Computational biology; Mathematics; Biology; Genetics; Gene; Pure mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001526845,0.0002388708,0.0001759865,0.0000595336,0.0001304815,0.0001698803,0.0002463213,0.0001728626,0.00006714839],"category_scores_gemma":[0.00004063341,0.0002453513,0.0001557588,0.000161334,0.00009653672,0.00001379006,0.00002609546,0.0002275444,0.00007207449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003978085,"about_ca_system_score_gemma":0.0001480395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000227033,"about_ca_topic_score_gemma":0.0001644771,"domain_scores_codex":[0.9984411,0.00007953763,0.0004144215,0.0005798645,0.0002063502,0.0002787033],"domain_scores_gemma":[0.9993505,0.0000308991,0.00007840199,0.0003513541,0.00007843806,0.0001103823],"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":[0.00008259025,0.0001460562,0.0003619628,0.00002488974,0.00005196543,0.000006955479,0.0002899887,0.000934417,0.9850686,0.0002747549,0.0001493477,0.01260843],"study_design_scores_gemma":[0.00007697804,0.0001613689,0.00009857014,0.00003738117,0.0001014635,0.000003271494,0.0001490178,0.04274534,0.9511335,0.001076136,0.004084275,0.0003326333],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.817522,0.001743967,0.179027,0.00005661381,0.0009520176,0.0001688195,0.0001529883,0.00006590645,0.0003106775],"genre_scores_gemma":[0.9902371,0.0001824163,0.008037961,0.0001704979,0.0009490597,0.000007390723,0.0002955796,0.00005936018,0.00006060783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1727152,"threshold_uncertainty_score":0.9999999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03375519850443906,"score_gpt":0.253275920852108,"score_spread":0.2195207223476689,"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."}}