Urban Built Environments in Early 1st Millennium <scp>b.c.e.</scp> Syro-Anatolia: Results of the Tayinat Archaeological Project, 2004–2016
Bibliographic record
Abstract
The archaeological site of Tell Tayinat in the province of Hatay in southern Turkey was the principal regional center in the Amuq Plain and North Orontes Valley during the Early Bronze and Iron Ages. This paper focuses on the latest known period of occupation at Tayinat, which during the Iron Age was the Syro-Anatolian city of Kunulua. In 2004, following a 67-year hiatus, the University of Toronto’s Tayinat Archaeological Project (TAP) resumed excavations at the site. Here we present the preliminary results of TAP’s investigations of the Iron Age II and III settlement, including the topography of the 1st millennium settlement, super- and sub-structural remains associated with Building II (a temple first discovered in the 1930s), a second, newly discovered temple (Building XVI), part of a large Assyrian-style courtyard building, and the remains of additional monumental architecture on the Iron Age citadel. The terminal phases of these structures date to the Iron Age III period, or the late 8th and 7th century occupation of Kunulua following the Assyrian conquest in 738 b.c.e., and collectively point to the transformation of Kunulua’s royal citadel into a Neo-Assyrian provincial administrative center, a pattern witnessed at contemporary sites elsewhere in southeastern Anatolia and northern Syria.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".