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Bibliographic record
Abstract
New Features Timelapse functionality is extended to tracking data: tracking timelapse data automatically detected when using 4D images and measurements without a column named "frame" What's Changed [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/BiAPoL/napari-clusters-plotter/pull/96 Increase code coverage: Making tests for plotter utilities by @Cryaaa in https://github.com/BiAPoL/napari-clusters-plotter/pull/101 Bugfix: Fix the license file by @haesleinhuepf in https://github.com/BiAPoL/napari-clusters-plotter/pull/99 adding acknowledgements to readme by @haesleinhuepf in https://github.com/BiAPoL/napari-clusters-plotter/pull/102 Improve documentation: add quick links to readme by @lazigu in https://github.com/BiAPoL/napari-clusters-plotter/pull/106 Bugfix: fix tests by @haesleinhuepf in https://github.com/BiAPoL/napari-clusters-plotter/pull/109 Bugfix: don't redraw plot in case the plot is invisible by @haesleinhuepf in https://github.com/BiAPoL/napari-clusters-plotter/pull/108 Reintroduction of feature: make option to have tracking data to plot by @Cryaaa in https://github.com/BiAPoL/napari-clusters-plotter/pull/105 <strong>Full Changelog</strong>: https://github.com/BiAPoL/napari-clusters-plotter/compare/0.5.0...0.5.1
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.147 | 0.024 |
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