{"id":"W6931144325","doi":"10.5281/zenodo.2859286","title":"fMRIPrep: a robust preprocessing pipeline for functional MRI","year":2019,"lang":"en","type":"other","venue":"Figshare","topic":"Paleontology and Stratigraphy of Fossils","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Pipeline (software); Preprocessor; Workflow; Pattern recognition (psychology); Pipeline transport","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":[0.002849505,0.002633323,0.00117604,0.003002524,0.00137871,0.003042684,0.003552173,0.002073673,0.1414437],"category_scores_gemma":[0.008772211,0.002013692,0.001745088,0.001833307,0.0006825781,0.001874906,0.003578947,0.002887422,0.1103036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000596401,"about_ca_system_score_gemma":0.001900905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002131179,"about_ca_topic_score_gemma":0.005384787,"domain_scores_codex":[0.9990373,0.0001635841,0.0001267131,0.0003024107,0.000274108,0.00009592868],"domain_scores_gemma":[0.9978249,0.0008499376,0.0001466348,0.0005059682,0.0005450799,0.0001274974],"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":[0.0005906869,0.00005864488,0.0007401472,0.001206394,0.0002319821,0.0004520233,0.0002384304,0.001927376,0.02425289,0.005126202,0.7758035,0.1893718],"study_design_scores_gemma":[0.0004431411,0.0001685817,0.00626101,0.0004740118,0.0002360868,0.002787501,0.0001065596,0.0263278,0.05688906,0.05424904,0.8515344,0.0005228362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002377866,0.00138163,0.6595755,0.0008567733,0.0006227121,0.0008002374,0.05891291,0.2580037,0.01746871],"genre_scores_gemma":[0.01744073,0.001182306,0.7370101,0.001757441,0.0005316563,0.003847898,0.09311869,0.1210088,0.02410232],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1414437,"threshold_uncertainty_score":0.4731764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05167276498330241,"score_gpt":0.2374358778540493,"score_spread":0.1857631128707469,"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."}}