Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Breaking changes Refactoring of the <code>Indicator</code> class. The <code>cfprobe</code> method has been renamed to <code>cfcheck</code> and the <code>validate</code> method has been renamed to <code>datacheck</code>. More importantly, instantiating <code>Indicator</code> 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 <code>missing_options</code>. xclim now requires xarray >= 0.16, ensuring that xclim.sdba is fully functional. The dev requirements now include <code>xdoctest</code> -- a rewrite of the standard library module, <code>doctest</code>. <code>xclim.core.locales.get_local_attrs</code> now uses the indicator's class name instead of the indicator itself and no longer accepts the <code>fill_missing</code> keyword. Behaviour is now the same as passing <code>False</code>. <code>Indicator.cf_attrs</code> is now a list of dictionaries. <code>Indicator.json</code> puts all the metadata attributes in the key "outputs" (a list of dicts). All variable metadata (names in <code>Indicator._cf_names</code>) 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 <code>ensembles.kkz_reduce_ensemble</code> method to select subsets of an ensemble based on the KKZ algorithm. Create new Indicator <code>Daily</code>, <code>Daily2D</code> subclasses for indicators using daily input data. The <code>Indicator</code> class now supports outputing multiple indices for the same inputs. <code>xclim.core.units.declare_units</code> now works with indices outputting multiple DataArrays. Doctests now make use of the <code>xdoctest_namespace</code> in order to more easily access mdoules and tesdata. Bug fixes Fix <code>generic.fit</code> dimension ordering. This caused errors when "time" was not the first dimension in a DataArray. Internal changes <code>datachecks.check_daily</code> now uses <code>xr.infer_freq</code>. Indicator subclasses <code>Tas</code>, <code>Tasmin</code>, <code>Tasmax</code>, <code>Pr</code> and <code>Streamflow</code> now inherit from <code>Daily</code>. Indicator subclasses <code>TasminTasmax</code> and <code>PrTas</code> now inherit from <code>Daily2D</code>. Docstring style now enforced using the <code>pydocstyle</code> with <code>numpy</code> doctsring conventions. Doctests are now performed for all docstring <code>Examples</code> using <code>xdoctest</code>. Failing examples must be explicitly skipped otherwise build will now fail. Indicator methods <code>update_attrs</code> and <code>format</code> 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 <code>Indicator</code> to support multiple outputs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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 it