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Enregistrement W2591206133 · doi:10.5281/zenodo.575897

Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.0

2017· article· en· W2591206133 sur OpenAlexaff
Krzysztof J. Gorgolewski

Notice bibliographique

RevueEdinburgh Research Explorer (University of Edinburgh) · 2017
Typearticle
Langueen
DomaineNeuroscience
ThématiqueEEG and Brain-Computer Interfaces
Établissements canadiensMontreal Neurological Institute and Hospital
Organismes subventionnairesnon disponible
Mots-clésComputer sciencePython (programming language)WorkflowNeuroimagingScripting languageSoftwareSoftware engineeringNeuroinformaticsSoftware developmentArtificial intelligenceData scienceProgramming languageDatabase

Résumé

récupéré en direct d'OpenAlex

0.13.1 (May 20, 2017) FIX: Make release compatible with conda-forge build process (https://github.com/nipy/nipype/pull/2017) ENH: Update some minimum versions in compliance with Debian Jessie (https://github.com/nipy/nipype/pull/2017) ENH: Circle builds use cached docker layers (https://github.com/nipy/nipype/pull/2017) ENH: Base docker to use FS6 and ANTS 2.2.0 (https://github.com/nipy/nipype/pull/2024) FIX: Mailmap and contributor acknowledgment (https://github.com/nipy/nipype/pull/2017) FIX: Preserve node properties in sub nodes of MapNode (https://github.com/nipy/nipype/pull/2019) FIX: Fix interfaces 3DUnifize, ICA_AROMA, BinaryMaths, RegAverage, BBRegister, AffineInitializer (https://github.com/nipy/nipype/pull/2025, https://github.com/nipy/nipype/pull/2027, https://github.com/nipy/nipype/pull/2036, https://github.com/nipy/nipype/pull/2037, https://github.com/nipy/nipype/pull/2031, https://github.com/nipy/nipype/pull/2010) ENH: Add Anisotropic Power interface (https://github.com/nipy/nipype/pull/2039) FIX: Bayesian estimation in SPM (https://github.com/nipy/nipype/pull/2030) 0.13.0 (May 11, 2017) ENH: Multi-stage recon-all directives (https://github.com/nipy/nipype/pull/1991) FIX: FEAT "folder does not exist" error (https://github.com/nipy/nipype/pull/2000) ENH: Niftyfit interfaces (https://github.com/nipy/nipype/pull/1910) FIX: Define ANTSPATH for BrainExtraction automatically (https://github.com/nipy/nipype/pull/1986) ENH: New trait for imaging files (https://github.com/nipy/nipype/pull/1949) ENH: Niftyseg interfaces (https://github.com/nipy/nipype/pull/1911) ENH: Niftyreg interfaces (https://github.com/nipy/nipype/pull/1913) MRG: Allow more support for CLI (https://github.com/nipy/nipype/pull/1908) ENH: 3dQwarpPlusMinus interface (https://github.com/nipy/nipype/pull/1974) FIX: PY3.6 support (https://github.com/nipy/nipype/pull/1977) FIX: PY3 and stream fixes for MRTrix2TrackVis (https://github.com/nipy/nipype/pull/1804) ENH: More mask options for CompCor interfaces (https://github.com/nipy/nipype/pull/1968 + https://github.com/nipy/nipype/pull/1992) ENH: Additional TOPUP outputs (https://github.com/nipy/nipype/pull/1976) ENH: Additional Eddy flags (https://github.com/nipy/nipype/pull/1967) ENH: ReconAll handlers for less common cases (https://github.com/nipy/nipype/pull/1966) ENH: FreeSurferSource now finds graymid/midthickness surfs (https://github.com/nipy/nipype/pull/1972) ENH: Additional fslmaths dimensional reduction operations (https://github.com/nipy/nipype/pull/1956) ENH: More options for RobustFOV interface (https://github.com/nipy/nipype/pull/1923) ENH: Add MRIsCombine to FreeSurfer utils (https://github.com/nipy/nipype/pull/1948) FIX: Level1Design EV parameter substitution (https://github.com/nipy/nipype/pull/1953) FIX: Dcm2niix outputs can be uncompressed (https://github.com/nipy/nipype/pull/1951) FIX: Ensure build fails in Circle when tests fail (https://github.com/nipy/nipype/pull/1981) ENH: Add interface to antsAffineInitializer (https://github.com/nipy/nipype/pull/1980) ENH: AFNI motion parameter support for FrameWiseDisplacement (https://github.com/nipy/nipype/pull/1840) ENH: Add ANTs KellyKapowski interface (https://github.com/nipy/nipype/pull/1845) FIX: AFNI interface bug setting OMP_NUM_THREADS to 1 (https://github.com/nipy/nipype/pull/1728) FIX: Select Eddy run command at runtime (https://github.com/nipy/nipype/pull/1871) FIX: Increase FLIRT's flexibility with apply_xfm (https://github.com/nipy/nipype/pull/1875) DOC: Update FSL preprocess docstrings (https://github.com/nipy/nipype/pull/1881) ENH: Support GIFTI outputs in SampleToSurface (https://github.com/nipy/nipype/pull/1886) FIX: Configparser differences between PY2 and PY3 (https://github.com/nipy/nipype/pull/1890) ENH: Add mris_expand interface (https://github.com/nipy/nipype/pull/1893) FIX: Split over-eager globs in FreeSurferSource (https://github.com/nipy/nipype/pull/1894) FIX: Store undefined by default so that xor checks don't trip (https://github.com/nipy/nipype/pull/1903) FIX: Gantt chart generator PY3 compatibility (https://github.com/nipy/nipype/pull/1907) FIX: Add DOF and --fsl-dof options to BBRegister (https://github.com/nipy/nipype/pull/1917) ENH: Auto-derive input_names in Function (https://github.com/nipy/nipype/pull/1918) FIX: Minor fixes for NonSteadyStateDetector (https://github.com/nipy/nipype/pull/1926) DOC: Add duecredit references for AFNI and FSL (https://github.com/nipy/nipype/pull/1930) ENH: Added zenodo (https://zenodo.org/) file (https://github.com/nipy/nipype/pull/1924) ENH: Disable symlinks on CIFS filesystems (https://github.com/nipy/nipype/pull/1941) ENH: Sphinx extension to plot workflows (https://github.com/nipy/nipype/pull/1896) ENH: Added non-steady state detector for EPI data (https://github.com/nipy/nipype/pull/1839) ENH: Enable new BBRegister init options for FSv6+ (https://github.com/nipy/nipype/pull/1811) REF: Splits nipype.interfaces.utility into base, csv, and wrappers (https://github.com/nipy/nipype/pull/1828) FIX: Makespec now runs with nipype in current directory (https://github.com/nipy/nipype/pull/1813) FIX: Flexible nifti opening with mmap if Numpy < 1.12.0 (https://github.com/nipy/nipype/pull/1796 + https://github.com/nipy/nipype/pull/1831) ENH: DVARS includes intensity normalization feature - turned on by default (https://github.com/nipy/nipype/pull/1827) FIX: DVARS is correctly using sum of squares instead of standard deviation (https://github.com/nipy/nipype/pull/1827) ENH: Refactoring of nipype.interfaces.utility (https://github.com/nipy/nipype/pull/1828) FIX: CircleCI were failing silently. Some fixes to tests (https://github.com/nipy/nipype/pull/1833) FIX: Issues in Docker image permissions, and docker documentation (https://github.com/nipy/nipype/pull/1825) ENH: Revised all Dockerfiles and automated deployment to Docker Hub from CircleCI (https://github.com/nipy/nipype/pull/1815) ENH: Update ReconAll interface for FreeSurfer v6.0.0 (https://github.com/nipy/nipype/pull/1790) FIX: Cast DVARS float outputs to avoid memmap error (https://github.com/nipy/nipype/pull/1777) FIX: FSL FNIRT intensity mapping files (https://github.com/nipy/nipype/pull/1799) ENH: Additional outputs generated by FSL EDDY (https://github.com/nipy/nipype/pull/1793) TST: Parallelize CircleCI build across 4 containers (https://github.com/nipy/nipype/pull/1769) 0.13.0-rc1 (January 4, 2017) FIX: Compatibility with traits 4.6 (https://github.com/nipy/nipype/pull/1770) FIX: Multiproc deadlock (https://github.com/nipy/nipype/pull/1756) TST: Replace nose and unittest with pytest (https://github.com/nipy/nipype/pull/1722, https://github.com/nipy/nipype/pull/1751) FIX: Semaphore capture using MultiProc plugin (https://github.com/nipy/nipype/pull/1689) REF: Refactor AFNI interfaces (https://github.com/nipy/nipype/pull/1678, https://github.com/nipy/nipype/pull/1680) ENH: Move nipype commands to group command using click (https://github.com/nipy/nipype/pull/1608) FIX: AFNI Retroicor interface fixes (https://github.com/nipy/nipype/pull/1669) FIX: Minor errors after migration to setuptools (https://github.com/nipy/nipype/pull/1671) ENH: Add AFNI 3dNote interface (https://github.com/nipy/nipype/pull/1637) ENH: Abandon distutils, only use setuptools (https://github.com/nipy/nipype/pull/1627) FIX: Minor bugfixes related to unicode literals (https://github.com/nipy/nipype/pull/1656) TST: Automatic retries in travis (https://github.com/nipy/nipype/pull/1659/files) ENH: Add signal extraction interface (https://github.com/nipy/nipype/pull/1647) ENH: Add a DVARS calculation interface (https://github.com/nipy/nipype/pull/1606) ENH: New interface to b0calc of FSL-POSSUM (https://github.com/nipy/nipype/pull/1399) ENH: Add CompCor (https://github.com/nipy/nipype/pull/1599) ENH: Add duecredit entries (https://github.com/nipy/nipype/pull/1466) FIX: Python 3 compatibility fixes (https://github.com/nipy/nipype/pull/1572) REF: Improved PEP8 compliance for fsl interfaces (https://github.com/nipy/nipype/pull/1597) REF: Improved PEP8 compliance for spm interfaces (https://github.com/nipy/nipype/pull/1593) TST: Replaced coveralls with codecov (https://github.com/nipy/nipype/pull/1609) ENH: More BrainSuite interfaces (https://github.com/nipy/nipype/pull/1554) ENH: Convenient load/save of interface inputs (https://github.com/nipy/nipype/pull/1591) ENH: Add a Framewise Displacement calculation interface (https://github.com/nipy/nipype/pull/1604) FIX: Use builtins open and unicode literals for py3 compatibility (https://github.com/nipy/nipype/pull/1572) TST: reduce the size of docker images & use tags for images (https://github.com/nipy/nipype/pull/1564) ENH: Implement missing inputs/outputs in FSL AvScale (https://github.com/nipy/nipype/pull/1563) FIX: Fix symlink test in copyfile (https://github.com/nipy/nipype/pull/1570, https://github.com/nipy/nipype/pull/1586) ENH: Added support for custom job submission check in SLURM (https://github.com/nipy/nipype/pull/1582) ENH: Added ANTs interface CreateJacobianDeterminantImage; replaces deprecated JacobianDeterminant (https://github.com/nipy/nipype/pull/1654)

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Logiciel · Signal consensuel: Logiciel
Score de désaccord entre enseignants0,151
Score d'incertitude au seuil0,506

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,009
Méta-épidémiologie (sens strict)0,0030,003
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0040,006
Science ouverte0,0070,008
Intégrité de la recherche0,0010,005
Charge utile insuffisante (le modèle a refusé de juger)0,1510,163

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,223
Tête enseignante GPT0,383
Écart entre enseignants0,161 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreLogiciel

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations62
Publié2017
Routes d'admission1
Résumé présentoui

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