{"id":"W3204079698","doi":"10.1038/s41467-021-26140-y","title":"Publisher Correction: Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data","year":2021,"lang":"en","type":"article","venue":"Nature Communications","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; McGill University","funders":"","keywords":"Signature (topology); Trainer; Computer science; Transcriptome; Computational biology; Gene; Artificial intelligence; Data mining; Biology; Genetics; Gene expression; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006254125,0.003218393,0.002638304,0.005726352,0.003397445,0.006106446,0.007446935,0.004683594,0.4702098],"category_scores_gemma":[0.1269521,0.002002251,0.002934247,0.005962892,0.001867105,0.005068229,0.005745099,0.008054163,0.201977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00241235,"about_ca_system_score_gemma":0.005303095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009752678,"about_ca_topic_score_gemma":0.01481026,"domain_scores_codex":[0.9952664,0.0008165437,0.0007647417,0.001038353,0.001745975,0.0003679619],"domain_scores_gemma":[0.9434828,0.01736487,0.001124665,0.009417422,0.02669763,0.001912585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004361606,0.000005653428,0.0001161305,0.0001899235,0.00003646187,0.0001191747,0.00003292765,0.0001990585,0.0002275981,0.001117037,0.992088,0.005824463],"study_design_scores_gemma":[0.0001462338,0.00003127834,0.001316666,0.00040896,0.0001062346,0.0006735573,0.00007951233,0.002627688,0.001942194,0.01042172,0.9821414,0.0001045306],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.001475301,0.0008715532,0.04248602,0.0330364,0.7937912,0.0001760667,0.08500706,0.02994074,0.01321578],"genre_scores_gemma":[0.05568334,0.003524607,0.1154787,0.0256867,0.101797,0.00149852,0.2149493,0.1010963,0.3802857],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4702098,"threshold_uncertainty_score":0.7556815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173466008668486,"score_gpt":0.2487695339670254,"score_spread":0.2270348738803405,"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."}}