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Record W6911742699 · doi:10.5281/zenodo.13863588

Ouranosinc/xscen: v0.10.0

2024· other· en· W6911742699 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsOuranos
Fundersnot available
KeywordsMercator projectionDocumentationOblique caseArgument (complex analysis)Schema (genetic algorithms)

Abstract

fetched live from OpenAlex

v0.10.0 (2024-09-30) Contributors to this version: Juliette Lavoie (@juliettelavoie), Pascal Bourgault (@aulemahal), Gabriel Rondeau-Genesse (@RondeauG), Trevor James Smith (@Zeitsperre). New features and enhancements The mask argument in stack_drop_nans can now be a list of dimensions. In that case, a dropna(how='all') operation will be used to create the mask on-the-fly. (PR/450). Few changes to clean_up: The convert_calendar function now uses xarray instead of xclim. (PR/450). The attrs_to_remove and remove_all_attrs_except arguments now use real regex. (PR/450). Multiple entries can now be given for change_attr_prefix. (PR/450). minimum_calendar now accepts a list as input. (PR/450). More calendars are now recognized in translate_time_chunk. (PR/450). new_dim in unstack_dates is now None by default and changes depending on the frequency. It becomes month if the data is exactly monthly, and keep the old default of season otherwise. (PR/450). Updated the list of libraries in show_versions to reflect our current environment. (PR/450). New xscen.catutils.patterns_from_schema to generate all possible patterns from a given schema (or one of xscen's default), to use with :py:func:parse_directory. (PR/431). New DataCatalog.copy_files to copy all files of catalog to a new destination, unzipping if needed and returning a new catalog. (PR/431). Convenience functions xs.io.zip_directory and xs.io.unzip_directory (for zarrs). (PR/431). New argument compute_indicators: rechunk_input to rechunk the inputs to resample-appropriate chunks before calling xclim. (PR/431). New xs.indicators.get_indicator_outputs to retrieve what variable name(s) and frequency to expect from an xclim indicator. (PR/431). xscen now supports launches tests from pytest with the --numprocesses option. See the pytest-xdist documentation _ for more information. (PR/464). Conservative regridding now supports oblique mercator projections. (PR/467). The automatic name for the weight file in regrid_dataset is now more explicit to avoid errors, but now requires cat:id and cat:domain arguments for both the source and target datasets. (PR/467). Bug fixes Fixed bug with reusing weights. (GH/411, PR/414). Fixed bug in update_from_ds when "time" is a coordinate, but not a dimension. (:pull: 417). Avoid modification of mutable arguments in search_data_catalogs (PR/413). ensure_correct_time now correctly handles cases where timesteps are missing. (PR/440). If using the argument tile_buffer with a shape method in spatial.subset, the shapefile will now be reprojected to a WGS84 grid before the buffer is applied. (PR/440). maybe_unstack now works if the dimension name is not the default. (PR/450). unstack_fill_nan now works if given a dictionary that contains both dimensions and coordinates. (PR/450). clean_up no longer modifies the original dataset. (PR/450). unstack_dates now works correctly for yearly datasets when winter_starts_year=True, as well as multi-year datasets. (PR/450). Fix xs.catalog.concat_data_catalogs for catalogs that have not been search yet. (PR/431). Fix indicator computation using freq=2Q* by assuming this means a semiannual frequency anchored at the given month (pandas assumes 2 quarter steps, any of them anchored at the given month). (PR/431). create_bounds_rotated_pole now uses the default value if the dataset has no north_pole_grid_longitude attribute, instead of crashing. (PR/455). Rewrote the global tas data file with latest HDF5/h5py to avoid errors when using h5py 3.11 and hdf5 1.14.2. (PR/1861). Remove reference of deprecated xclim functions (convert_calendar, get_calendar) and adapt the code for supporting xclim 0.52.2 and its subsequent development version. (PR/465). Breaking changes convert_calendar in clean_up now uses xarray instead of xclim. Keywords aren't compatible between the two, but given that xclim will abandon its function, no backwards compatibility was sought. (PR/450). attrs_to_remove and remove_all_attrs_except in clean_up now use real regex. It should not be too breaking since a fullmatch() is used, but * is now .*. (PR/450). Python 3.9 is no longer supported. (PR/456). Functions and arguments that were deprecated in xscen v0.8.0 or earlier have been removed. (PR/461). pytest-xdist is now a development dependency. (PR/464). xs.regrid.create_bounds_rotated_pole has been renamed to xs.regrid.create_bounds_gridmapping. (PR/467). The weights_location argument in regrid_dataset is no longer positional. (PR/467). The xs.regrid.create_mask function now requires explicit arguments instead of a dictionary. (PR/467). Internal changes DataCatalog.to_dataset can now accept a preprocess argument even if create_ensemble_on is given. The user assumes calendar handling. (PR/431). Include domain in weight_location in regrid_dataset. (PR/414). Added pins to xarray, xclim, h5py, and netcdf4. (PR/414). Add .zip and .zarr.zip as possible file extensions for Zarr datasets. (PR/426). Explicitly assign coords of multiindex in xs.unstack_fill_nan. (PR/427). French translations are compiled offline. A new check ensures no PR are merged with missing messages. (GH/342, PR/443). Continued work to add tests. (PR/450). Updated the cookiecutter template via cruft: (PR/452) GitHub Workflows that use rely on PyPI-based dependencies now use commit hashes. Dependabot will now group updates by type. Dependencies have been updated and synchronized. Contributor guidance documentation has been adjusted. numpydoc-validate has been added to the linting tools. Linting checks are more reliant on ruff suggestions and stricter. flake8-alphabetize has been replaced by ruff. License information has been updated in the library top-level __init__.py. Docstrings have been adjusted to meet the numpydoc standard. (PR/452). CI changes The bump-version.yml workflow now uses the Ouranosinc GitHub Helper Bot to sign bump version commits. (PR/462).

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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)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.618
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0100.009
Open science0.0120.009
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.6180.779

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 head0.021
GPT teacher head0.264
Teacher spread0.242 · 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.

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicYersinia bacterium, plague, ectoparasites researchFrench-language works237,207