{"id":"W3020867055","doi":"10.1101/2020.05.07.083436","title":"CellExplorer: a graphical user interface and a standardized pipeline for visualizing and characterizing single neurons","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"H. Lundbeck A/S; Lundbeckfonden","keywords":"Pipeline (software); Computer science; Graphical user interface; Interface (matter); Set (abstract data type); Process (computing); Ground truth; Software; Human–computer interaction; Artificial intelligence; Operating system; Programming language","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":[0.001991546,0.002452184,0.00136016,0.002579228,0.0005302977,0.001940153,0.003351224,0.001260607,0.03749662],"category_scores_gemma":[0.003859031,0.001145697,0.001273051,0.001164037,0.0006130794,0.001743408,0.002330631,0.00185183,0.01227669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005423087,"about_ca_system_score_gemma":0.001085373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002580462,"about_ca_topic_score_gemma":0.003506026,"domain_scores_codex":[0.9993743,0.00008873152,0.00008905026,0.0001470887,0.0002378175,0.00006309348],"domain_scores_gemma":[0.9983311,0.0008087333,0.0001012016,0.0002602217,0.0003329719,0.0001658164],"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":[0.001710313,0.0002682678,0.005122838,0.001848935,0.0005800977,0.0008898954,0.0008142132,0.008043719,0.1113661,0.01343264,0.6288908,0.2270322],"study_design_scores_gemma":[0.001293901,0.0002593227,0.01655713,0.0005126305,0.0002366703,0.001733889,0.000298036,0.2382718,0.2105315,0.04063527,0.4889897,0.0006801161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004419647,0.0002398468,0.5232185,0.0002852672,0.00009364042,0.0003315278,0.0302064,0.4385258,0.002679449],"genre_scores_gemma":[0.05953802,0.0007184208,0.7789224,0.0009931856,0.0001381187,0.004681651,0.07273647,0.07414529,0.008126478],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03749662,"threshold_uncertainty_score":0.1254387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03729773127332035,"score_gpt":0.2574016306055436,"score_spread":0.2201038993322232,"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."}}