{"id":"W3174207866","doi":"10.1038/s41596-021-00561-x","title":"Prioritization of cell types responsive to biological perturbations in single-cell data with Augur","year":2021,"lang":"en","type":"article","venue":"Nature Protocols","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Canada's Michael Smith Genome Sciences Centre; Michael Smith Health Research BC; International Collaboration On Repair Discoveries","funders":"Canadian Institutes of Health Research","keywords":"Prioritization; Computer science; Computational biology; Cell type; Protocol (science); Workflow; Chromatin; Genomics; Single-cell analysis; Systems biology; Cell; Biology; Genome; Gene; Genetics","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":[0.0001202653,0.0001127314,0.0001433338,0.00004355434,0.00002954496,0.00001983472,0.0002497184,0.0003179235,0.00001404605],"category_scores_gemma":[0.0002441032,0.0000918505,0.00002582198,0.000245917,0.00003384645,0.000005920682,0.0001056228,0.0001917581,0.000002200612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001329137,"about_ca_system_score_gemma":0.0001919787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006384118,"about_ca_topic_score_gemma":0.000131008,"domain_scores_codex":[0.9990881,0.00009123073,0.0001796685,0.0003870825,0.0001117687,0.0001421275],"domain_scores_gemma":[0.9991617,0.00003011861,0.00005799786,0.0004685859,0.0002335792,0.00004802036],"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":[0.0004575042,0.0003390598,0.006669289,0.00004892346,0.000006849747,0.00000765112,0.00005475579,0.00004369842,0.9914934,0.00004423084,0.0004648313,0.000369792],"study_design_scores_gemma":[0.0008774839,0.0006435422,0.002679344,0.00007231669,0.000006914617,0.000004863703,0.00004321222,0.00003682552,0.9549418,0.00003397495,0.04051051,0.0001491955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9677786,0.000556311,0.00424571,0.000481579,0.00008540267,0.0228679,0.0002311255,0.00002111553,0.003732313],"genre_scores_gemma":[0.9813773,0.00001228189,0.01407067,0.0004564105,0.0001018329,0.002670358,0.0006429169,0.00001942584,0.0006488042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04004567,"threshold_uncertainty_score":0.3745555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0334116976477594,"score_gpt":0.30010877367943,"score_spread":0.2666970760316706,"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."}}