Ḥuqoq – 2017
Bibliographic record
Abstract
In June 2017, the seventh season of excavations was conducted at Ḥorbat Ḥuqoq (License No. G-24/2017; map ref. 24500–50/75430–65; Magness at al. 2017). The excavation was undertaken and underwritten by the University of North Carolina at Chapel Hill, Baylor University (Texas), Brigham Young University (Utah) and the University of Toronto (Canada). Additional funding was provided by the National Geographic Society, the Loeb Classical Library Foundation, the International Catacomb Society, the Foundation for Biblical Archaeology (S. Bishop) and private donors. The excavation was directed by J. Magness, with the assistance of S. Kisilevitz (assistant director), M. Golan (administration), M. Grey and D. Mizzi (area supervision), J. Haberman (field photography), M. Robinson-Mohr (registration), D. Schindler (ceramics), K. Britt (mosaics), M. Wells (architecture), S. O’Connell (painted plaster), E. Hubbard (geoarchaeology and micromorphology), R. Mohr (drawing), V. Pirsky (drafting), O. Cohen (site and small finds conservation) and Griffin Aerial Imaging (aerial photography). The volunteers were undergraduate and graduate students from the USA, Canada and Slovakia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.085 | 0.015 |
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".