{"id":"W4403761643","doi":"10.1101/2024.10.24.620111","title":"scMoE: single-cell mixture of experts for learning hierarchical, cell-type-specific, and interpretable representations from heterogeneous scRNA-seq data","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Type (biology); Computer science; Cell type; Artificial intelligence; Cell; Chemistry; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002526637,0.001262805,0.001100291,0.0007415794,0.0004026383,0.0009439285,0.001919365,0.002335095,0.002242249],"category_scores_gemma":[0.005089423,0.0007847388,0.001652335,0.0005619354,0.0008263391,0.001157421,0.001662271,0.002675042,0.0009358008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009882395,"about_ca_system_score_gemma":0.001093851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006869098,"about_ca_topic_score_gemma":0.009216207,"domain_scores_codex":[0.9993861,0.0002369612,0.00002056857,0.0001936123,0.000100501,0.00006217371],"domain_scores_gemma":[0.9981072,0.001322936,0.00009925067,0.0001610689,0.0002051965,0.000104278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002690451,0.0000787845,0.001382846,0.0001246715,0.0002050973,0.0001491531,0.0001391505,0.9151391,0.01125748,0.006286594,0.005471881,0.05949625],"study_design_scores_gemma":[0.000005935253,0.000008335119,0.00008784464,0.000002990567,0.000003718049,0.00001033792,0.000004888673,0.9955851,0.001011337,0.002955824,0.0003185291,0.000005103204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01991922,0.00029978,0.976382,0.0003359263,0.00003858019,0.00005551596,0.0005591374,0.002010254,0.0003995354],"genre_scores_gemma":[0.3629652,0.0003448153,0.6236723,0.0010391,0.0001699172,0.000545078,0.005050892,0.0009105229,0.005302293],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006869098,"threshold_uncertainty_score":0.01365823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02640327145346393,"score_gpt":0.2405601743918022,"score_spread":0.2141569029383383,"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."}}