Bibliographic record
Abstract
What's Changed First off - thanks to all those who made this release possible!! All the contributions are greatly appreciated 🙏 Add parquet driver by @charles-turner-1 in https://github.com/intake/intake-esm/pull/728 Update README to correct cat_subset representation output by @sadielbartholomew in https://github.com/intake/intake-esm/pull/673 Update changelog by @charles-turner-1 in https://github.com/intake/intake-esm/pull/731 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/intake/intake-esm/pull/733 Update to zarr v3 by @charles-turner-1 in https://github.com/intake/intake-esm/pull/735 Force iterable column to always be tuple by @charles-turner-1 in https://github.com/intake/intake-esm/pull/734 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/intake/intake-esm/pull/740 Bump pypa/gh-action-pypi-publish from 1.12.4 to 1.13.0 in /.github/workflows by @dependabot[bot] in https://github.com/intake/intake-esm/pull/741 Pin polars < 1.33 by @charles-turner-1 in https://github.com/intake/intake-esm/pull/749 Replace Pydantic .dict() with .model_dump() by @will-s-hart in https://github.com/intake/intake-esm/pull/746 Bump the actions group with 4 updates by @dependabot[bot] in https://github.com/intake/intake-esm/pull/747 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/intake/intake-esm/pull/748 Fix Pydantic 2.12 compatibility by updating @model_validator signature by @antarcticrainforest in https://github.com/intake/intake-esm/pull/751 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/intake/intake-esm/pull/756 Bump the actions group with 2 updates by @dependabot[bot] in https://github.com/intake/intake-esm/pull/755 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/intake/intake-esm/pull/760 Bump actions/checkout from 5 to 6 in the actions group by @dependabot[bot] in https://github.com/intake/intake-esm/pull/759 Change chunking default to auto for compatible xarray versions by @charles-turner-1 in https://github.com/intake/intake-esm/pull/737 Fix polars remote csv panic #744 by @charles-turner-1 in https://github.com/intake/intake-esm/pull/754 Feature/xarray kerchunk engine by @chiaweh2 in https://github.com/intake/intake-esm/pull/758 New Contributors @will-s-hart made their first contribution in https://github.com/intake/intake-esm/pull/746 @antarcticrainforest made their first contribution in https://github.com/intake/intake-esm/pull/751 @chiaweh2 made their first contribution in https://github.com/intake/intake-esm/pull/758 Full Changelog: https://github.com/intake/intake-esm/compare/v2025.7.9...v2025.12.12
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 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.719 | 0.843 |
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".