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Record 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 on OpenAlexaff
Krzysztof J. Gorgolewski

Bibliographic record

VenueEdinburgh Research Explorer (University of Edinburgh) · 2017
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsComputer sciencePython (programming language)WorkflowNeuroimagingScripting languageSoftwareSoftware engineeringNeuroinformaticsSoftware developmentArtificial intelligenceData scienceProgramming languageDatabase

Abstract

fetched live from 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)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.151
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0070.008
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.1510.163

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.223
GPT teacher head0.383
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreSoftware

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations62
Published2017
Admission routes1
Has abstractyes

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