{"id":"W3009890223","doi":"10.1016/j.softx.2020.100434","title":"UF2C — User-Friendly Functional Connectivity: A neuroimaging toolbox for fMRI processing and analyses","year":2020,"lang":"en","type":"article","venue":"SoftwareX","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Toolbox; Computer science; Preprocessor; User Friendly; Functional magnetic resonance imaging; Software; MIT License; Functional connectivity; Human–computer interaction; Task (project management); Neuroimaging; Field (mathematics); Event (particle physics); License; Artificial intelligence; Programming language; Neuroscience; Operating system","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":[0.002250413,0.002059485,0.001144559,0.002591328,0.000573913,0.001914661,0.003274593,0.001209853,0.1532266],"category_scores_gemma":[0.01097512,0.001358861,0.00133331,0.001375677,0.0005896785,0.002329087,0.002789053,0.001982105,0.04738664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005372646,"about_ca_system_score_gemma":0.001345984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002079342,"about_ca_topic_score_gemma":0.004927285,"domain_scores_codex":[0.9993813,0.000135209,0.00008149417,0.0001351558,0.0002043253,0.00006247911],"domain_scores_gemma":[0.9967605,0.001735395,0.0003016818,0.0004536252,0.0005832542,0.000165423],"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":[0.0008382576,0.0001496566,0.00164512,0.002342861,0.0004169614,0.0005798439,0.0005535205,0.006354859,0.02096822,0.01752653,0.6822729,0.2663513],"study_design_scores_gemma":[0.0009959989,0.0003622501,0.0188628,0.001060986,0.0003838087,0.005430934,0.0001689078,0.1714309,0.06071134,0.1137953,0.6260794,0.0007173597],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00446265,0.0006732608,0.7629159,0.000330819,0.000233537,0.0005950922,0.02968523,0.1911575,0.009945943],"genre_scores_gemma":[0.03812239,0.0007033104,0.7638555,0.0008143044,0.0002144076,0.006051789,0.03474441,0.1406668,0.0148271],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1532266,"threshold_uncertainty_score":0.5125939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1217404192981166,"score_gpt":0.3250821209447101,"score_spread":0.2033417016465935,"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."}}