Map dataset for "Assessing the role of plant seasonalities on the regional organisation of the Tapajó Society"
Bibliographic record
Abstract
The dataset comprises the georeferenced location of 158 archaeological sites in the Santarem Region, Lower Amazon. It compiles information on the locations of archaeological sites gathered from published literature and the Brazilian Institute of National Historical and Artistic Heritage (IPHAN) database. The published materials are: Figueiredo, C. G. (2019).Regional complementarity and place-making in the Northern region of the Tapajós National Forest Reservation, Lower Amazon, Brazil. Dissertation, University of Toronto. Gomes, D. M. C. (2017). Politics and ritual in large villages in Santarém, Lower Amazon, Brazil. Cambridge Archaeological Journal, 27(2), 275–293. Nimuendaju. C. (2004). In pursuit of a past Amazon: Archaeological researches in the Brazilian Guyana and in the Amazon region. (A posthumous work compiled and translated by Stig Rydén and Per Stenborg). Etnologiska Studier, 45. Schaan, D. P. (2016). Discussing centre-periphery relations within the Tapajó domain, Lower Amazon. In P. Stenborg (Ed.), Beyond waters: Archaeology and environmental history of the Amazonian inland. Gotarc Series A, Gothenburg Archaeological Studies 6 (pp. 23–36). Stenborg, P. (2016). Towards a regional history of pre-Columbian settlements in the Santarém and Belterra regions, Pará, Brazil. In P. Stenborg (Ed.), Beyond waters: Archaeology and environmental history of the Amazonian inland. Gotarc Series, A. Gothenburg Archaeological Studies, 6 (pp. 9–22). Stenborg, P., Schaan, D. P., & Figueiredo, C. G. (2018). Contours of the past: LIDAR data expands the limits of late pre-Columbian human settlement in the Santarém region, Lower Amazon. Journal of Field Archaeology, 43(1), 44–57.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.089 | 0.049 |
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".