{"id":"W4242130571","doi":"10.21203/rs.3.rs-151085/v1","title":"Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; McGill University","funders":"","keywords":"Signature (topology); Transcriptome; Computational biology; Gene signature; Gene; Computer science; Artificial intelligence; Biology; Gene expression; Genetics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005594603,0.0005814548,0.0004405515,0.0004567067,0.0001239611,0.0007532498,0.0005075608,0.000706656,0.0007824021],"category_scores_gemma":[0.001895384,0.0003032659,0.000595476,0.0005814193,0.000451552,0.0008062273,0.0006766839,0.001084113,0.0005004186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003668367,"about_ca_system_score_gemma":0.0004819655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001455153,"about_ca_topic_score_gemma":0.002358817,"domain_scores_codex":[0.9998428,0.00003658006,0.000005449522,0.00007086944,0.00002203818,0.00002219355],"domain_scores_gemma":[0.9993615,0.0004063188,0.000065606,0.00008287952,0.00005234878,0.00003141968],"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":[0.0003183151,0.000128034,0.01618742,0.0003156371,0.0002033114,0.0003587517,0.0002679518,0.7061865,0.1220689,0.01909903,0.0054423,0.1294239],"study_design_scores_gemma":[0.000005199017,0.00001363509,0.001620156,0.000007551256,0.00001143114,0.00003800885,0.00002859053,0.975889,0.005654292,0.01579223,0.0009313013,0.000008563518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1645118,0.0007732802,0.8294801,0.000421415,0.0000586721,0.00002468818,0.002674038,0.001299652,0.0007563778],"genre_scores_gemma":[0.8243263,0.0009141198,0.1636536,0.0001686257,0.00008593669,0.00009795848,0.007964781,0.0002424183,0.002546313],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001455153,"threshold_uncertainty_score":0.002958775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05055686224859438,"score_gpt":0.3125117000731479,"score_spread":0.2619548378245535,"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."}}