Bibliographic record
Abstract
Breaking changes Refactoring of the Indicator class. The cfprobe method has been renamed to cfcheck and the validate method has been renamed to datacheck. More importantly, instantiating Indicator creates a new subclass on the fly and stores it in a registry, allowing users to subclass existing indicators easily. The algorithm for missing values is identified by its registered name, e.g. "any", "pct", etc, along with its missing_options. xclim now requires xarray >= 0.16, ensuring that xclim.sdba is fully functional. The dev requirements now include xdoctest -- a rewrite of the standard library module, doctest. xclim.core.locales.get_local_attrs now uses the indicator's class name instead of the indicator itself and no longer accepts the fill_missing keyword. Behaviour is now the same as passing False. Indicator.cf_attrs is now a list of dictionaries. Indicator.json puts all the metadata attributes in the key "outputs" (a list of dicts). All variable metadata (names in Indicator._cf_names) might be strings or lists of strings when accessed as object attributes. Passing doctests are now strictly enforced as a build requirement in the Travis CI testing ensemble. New features and enhancements New ensembles.kkz_reduce_ensemble method to select subsets of an ensemble based on the KKZ algorithm. Create new Indicator Daily, Daily2D subclasses for indicators using daily input data. The Indicator class now supports outputing multiple indices for the same inputs. xclim.core.units.declare_units now works with indices outputting multiple DataArrays. Doctests now make use of the xdoctest_namespace in order to more easily access mdoules and tesdata. Bug fixes Fix generic.fit dimension ordering. This caused errors when "time" was not the first dimension in a DataArray. Internal changes datachecks.check_daily now uses xr.infer_freq. Indicator subclasses Tas, Tasmin, Tasmax, Pr and Streamflow now inherit from Daily. Indicator subclasses TasminTasmax and PrTas now inherit from Daily2D. Docstring style now enforced using the pydocstyle with numpy doctsring conventions. Doctests are now performed for all docstring Examples using xdoctest. Failing examples must be explicitly skipped otherwise build will now fail. Indicator methods update_attrs and format are now classmethods, attrs to update must be passed. Indicators definitions without an accompanying translation (presently French) will cause build failures. Major refactoring of the internal marchinery of Indicator to support multiple outputs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.187 | 0.211 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".