{"id":"W4226241100","doi":"10.3389/fninf.2022.753770","title":"LaminaRGeneVis: A Tool to Visualize Gene Expression Across the Laminar Architecture of the Human Neocortex","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Health Canada; Canadian Open Neuroscience Platform; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Neocortex; Computational biology; Computer science; Gene expression; Gene; Expression (computer science); Laminar organization; Function (biology); Laminar flow; RNA; Biology; Neuroscience; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.000263645,0.0001564214,0.0001693621,0.0000395619,0.0003690168,0.00002495245,0.0007295964,0.00005890529,0.000005902496],"category_scores_gemma":[0.00005384801,0.0001062382,0.0001258756,0.000233598,0.00009103063,0.000005463681,0.0005054591,0.0002574032,5.561722e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002185758,"about_ca_system_score_gemma":0.0000443389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009084382,"about_ca_topic_score_gemma":0.000009199523,"domain_scores_codex":[0.998777,0.0001190932,0.0003917966,0.0001638162,0.0002709271,0.0002773425],"domain_scores_gemma":[0.9991792,0.00001007558,0.0001460832,0.0006013687,0.00002692976,0.00003629417],"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":[0.0002083047,0.0001741389,0.01755451,0.00008582712,0.00002880489,0.000004802646,0.007071076,0.01860692,0.929089,0.00003346623,0.01981835,0.007324835],"study_design_scores_gemma":[0.001840847,0.001205814,0.01376612,0.00005795148,0.00003668958,0.00005748801,0.004600542,0.003127825,0.7012482,0.0002723993,0.2731758,0.0006103219],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992062,0.0001576998,0.006191806,0.0001548743,0.0006794893,0.0004879637,0.00008290559,0.000008349892,0.0001748557],"genre_scores_gemma":[0.994485,0.00003251938,0.003674568,0.001151612,0.00007674236,0.00006448662,0.00004441393,0.00002754839,0.0004430818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2533574,"threshold_uncertainty_score":0.4332268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008092522347092408,"score_gpt":0.240693390222165,"score_spread":0.2326008678750726,"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."}}