{"id":"W4220888076","doi":"10.1101/2022.03.13.484162","title":"Multi-level cellular and functional annotation of single-cell transcriptomes","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; Brain Tumour Research; Canada First Research Excellence Fund","keywords":"Annotation; Toolbox; Computer science; Workflow; Computational biology; Modular design; Artificial intelligence; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003147956,0.0004451487,0.0004138673,0.0001686069,0.0001494868,0.00006139293,0.0002825655,0.0004649778,0.00005977239],"category_scores_gemma":[0.00005142901,0.0005233398,0.0002008763,0.0001772451,0.0001630162,0.00001026092,0.000228947,0.0004084444,0.000002512384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005992354,"about_ca_system_score_gemma":0.0002987413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003959386,"about_ca_topic_score_gemma":0.000004172317,"domain_scores_codex":[0.9978337,0.0001318228,0.0005052497,0.0008817938,0.0003130876,0.0003343727],"domain_scores_gemma":[0.998569,0.00001933907,0.0003138691,0.0006510907,0.000293782,0.0001529593],"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":[0.0001133935,0.0004415255,0.005409392,0.0004110681,0.000115581,0.000006857578,0.00001622393,0.0002201591,0.9931115,0.0000233429,0.0001268186,0.000004129032],"study_design_scores_gemma":[0.001155445,0.0002149633,0.03488858,0.00005273967,0.0001167546,2.378341e-8,0.000009802522,0.0002622686,0.9581617,7.338859e-7,0.004573036,0.0005639644],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9755677,0.003694599,0.01840828,0.00004478763,0.001097485,0.0004232845,0.0006982908,0.00005386147,0.00001174108],"genre_scores_gemma":[0.9902769,0.0003515222,0.008753315,0.0001116816,0.0002557186,0.00008224417,0.00001451648,0.0001100799,0.00004399756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03494982,"threshold_uncertainty_score":0.9997218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03058241076706832,"score_gpt":0.2124298176876054,"score_spread":0.1818474069205371,"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."}}