Bibliographic record
Abstract
What's Changed Updated rotation angle being read from edi by @kujaku11 in https://github.com/kujaku11/mt_metadata/pull/231 reduce logging from warning to info by @kkappler in https://github.com/kujaku11/mt_metadata/pull/232 Patches by @kkappler in https://github.com/kujaku11/mt_metadata/pull/233 Fix issue 235 by @kkappler in https://github.com/kujaku11/mt_metadata/pull/236 Fix issue 238 by @kkappler in https://github.com/kujaku11/mt_metadata/pull/240 Fix issue 241 (Move window into stft class) by @kkappler in https://github.com/kujaku11/mt_metadata/pull/242 towards mth5 spectrograms by @kkappler in https://github.com/kujaku11/mt_metadata/pull/244 Fix issue 239 by @kujaku11 in https://github.com/kujaku11/mt_metadata/pull/245 minor changes by @kkappler in https://github.com/kujaku11/mt_metadata/pull/234 remove anti_alias_filter accessors from FCDecimation and AuroraDecima… by @kkappler in https://github.com/kujaku11/mt_metadata/pull/247 Fix issue 238 housekeeping (continued) by @kkappler in https://github.com/kujaku11/mt_metadata/pull/248 Make obspy optional. by @jcapriot in https://github.com/kujaku11/mt_metadata/pull/252 Follow on PR #249 by @kujaku11 in https://github.com/kujaku11/mt_metadata/pull/251 Fix issue 222 by @kkappler in https://github.com/kujaku11/mt_metadata/pull/256 modify per issue #257 by @kkappler in https://github.com/kujaku11/mt_metadata/pull/258 Need to make a workflow to output files for FDSN DMC by @kujaku11 in https://github.com/kujaku11/mt_metadata/pull/254 Weights by @kkappler in https://github.com/kujaku11/mt_metadata/pull/259 Features by @kujaku11 in https://github.com/kujaku11/mt_metadata/pull/246 Patches by @kkappler in https://github.com/kujaku11/mt_metadata/pull/261 New Contributors @jcapriot made their first contribution in https://github.com/kujaku11/mt_metadata/pull/252 Full Changelog: https://github.com/kujaku11/mt_metadata/compare/v0.3.8...v0.4.0
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.625 | 0.739 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".