The Field of War: LiDAR Identification of Earthwork Defences on Tongatapu Island, Kingdom of Tonga
Bibliographic record
Abstract
Warfare and conflict are associated with complex societies in in Polynesia where competition and coercion were common in island chiefdoms. In prehistoric Oceania, Tonga was unique for an Archaic state that under the Tu'i Tonga dynasty established control over an entire archipelago from A.D. 1200 to A.D. 1799 prior to a prolonged period of warfare. Lidar data was used to identify earthwork fortifications over the entirety of Tongatapu and to examine the conflict landscape using lidar-derived attributes in tandem with archaeological and historical information. The distribution of earthwork defences indicates a complex history of conflict and political machinations across Tongatapu beginning with the Tu’i Tonga chiefs at Lapaha, but resulting in a mid-19th century civil war ending with a new royal dynasty. Fortifications offer important evidence of social-political change, and the heritage condition of earthwork defences, many of which are under threat from development, was assessed with lidar.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".