Bibliographic record
Abstract
Version 0.79 Released August 18, 2025 Add Bhutan holidays (#2635 by @Prateekshit73, @arkid15r, @code-with-aneesh, @KJhellico, @prateekshit-v) Add Gambia holidays (#2777 by @kritibirda26, @arkid15r) Add Guinea-Bissau holidays (#2776 by @kritibirda26, @arkid15r, @KJhellico) Add Iraq holidays (#2763 by @kritibirda26, @arkid15r) Add Kiribati holidays (#2778 by @kritibirda26, @arkid15r) Add Liberia holidays (#2774 by @kritibirda26) Add South Georgia and the South Sandwich Islands holidays (#2761 by @tr33k) Add Syrian Arab Republic holidays (#2791 by @Wasif-Shahzad) Add Turkmenistan holidays (#2757 by @Wasif-Shahzad) Update Azerbaijan holidays: fix observed Islamic holidays (#2822 by @KJhellico, @arkid15r) Update Bahrain holidays (#2784 by @KJhellico) Update Bhutan holidays: reference link archival (#2795 by @PPsyrius) Update Canada holidays: adjust introduction year of National Aboriginal Day in NT (#2804 by @KJhellico) Update Chile holidays: abolition of Dec 31 bank holiday (#2793 by @mbfarah) Update Chile holidays: add special holidays (#2798 by @mbfarah) Update Ethiopia holidays, add ETHIOPIAN_CALENDAR support, Julian Date Drift adjustment pre-1899 and post-2099 (#2794 by @PPsyrius) Update Turkmenistan holidays (#2785 by @KJhellico) Update badges: add downloads badge temporary fix (#2817 by @arkid15r) Update pre-commit: add pyproject-fmt (#2814 by @arkid15r) Update release notes generator (#2802 by @KJhellico) Add HolidayBase::is_weekend method (#2780 by @KJhellico, @arkid15r) Implement confirmed years range support for custom calendars (#2759 by @KJhellico, @arkid15r) Remove setup.py (#2823 by @arkid15r) Split tests/test_holiday_groups.py (#2803 by @arkid15r) New Contributors @mbfarah made their first contribution in https://github.com/vacanza/holidays/pull/2793 Full Changelog: https://github.com/vacanza/holidays/compare/v0.78...v0.79
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.610 | 0.669 |
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".