{"id":"W2936720016","doi":"10.1101/613083","title":"Exploring and analysing immune single cell multi-omics data with VDJView","year":2019,"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":"","funders":"National Health and Medical Research Council; Institute of Infection and Immunity; University of New South Wales; auDA Foundation","keywords":"Biology; Computational biology; Metadata; Immune system; T-cell receptor; Antigen; Transcriptome; CD8; T cell; Gene; Gene expression; Computer science; Immunology; Genetics; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004482433,0.0006421961,0.0006633396,0.0001446399,0.0001522239,0.0002692705,0.0009236033,0.0004413112,0.000004449026],"category_scores_gemma":[0.00006708431,0.000643725,0.0001177174,0.0002184382,0.0001470642,0.00003747556,0.001171302,0.0005480963,0.0000108731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006607714,"about_ca_system_score_gemma":0.0003482804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000107184,"about_ca_topic_score_gemma":0.00001482692,"domain_scores_codex":[0.9970256,0.000105258,0.000515121,0.001574615,0.0002431007,0.0005363102],"domain_scores_gemma":[0.996407,0.00002160255,0.0003697094,0.002739334,0.0002531447,0.0002091953],"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":[0.00007518772,0.0002153709,0.006213995,0.000538689,0.0002211629,0.00001544418,0.000008919854,0.0003053805,0.9923719,0.000004757891,0.0000177076,0.00001149712],"study_design_scores_gemma":[0.00135234,0.0002050847,0.01250185,0.0004688293,0.0003991814,8.831955e-8,0.00001110975,0.00240341,0.9750792,1.229306e-7,0.006332391,0.001246365],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758449,0.007914288,0.01453726,0.00004442724,0.0006884724,0.0005433652,0.0003310529,0.00008613175,0.00001006705],"genre_scores_gemma":[0.9767733,0.003730199,0.01876577,0.0001010837,0.0003637737,0.00004384058,0.00001694384,0.0001931131,0.00001201989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01729266,"threshold_uncertainty_score":0.9996014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06618352060445871,"score_gpt":0.2285037066036898,"score_spread":0.162320185999231,"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."}}