Bibliographic record
Abstract
The 29th excavation season of the 'Selz Foundation Hazor Excavations in Memory of Yigael Yadin' (Permit no. G-46/2018; map ref. 253129/769151) took place in June and July of 2018. The excavations are sponsored by the Philip and Muriel Berman Center for Biblical Archaeology at the Hebrew University of Jerusalem and by the Israel Exploration Society. The 2018 expedition benefited from the financial assistance of the Selz Foundation (New York), the Steven B. Dana Archaeology Fund (United States), the Edith and Reuben Hecht Fund (Israel) and individual donors. The excavation was directed by A. Ben-Tor and S. Bechar (Area M3 supervisor), assisted by S. Greenberg (Area M4 supervisor), L. Gonen (Area M3 assistant supervisor), N. Terchov (office management and registration), I. Strand (surveying and drafting), O. Cohen (conservation), Y. Sfez (sifting), M. Cimadevilla (photography) and S. Yadid and R. Jenkins (administration). The expedition numbered some 70 participants from Canada, the United States, France, Finland, Spain, Italy, Germany, South Africa, South Korea, Australia and Israel. The excavations are conducted in the Tel Hazor National Park with the full cooperation of the Israel Nature and Parks Authority. The expedition was housed at Kibbutz Gonen.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.389 | 0.157 |
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".