Holocene palaeoenvironmental evolution in the São Paulo State (Brazil), based on anthracology and soil δ13C analysis
Bibliographic record
Abstract
This paper presents a reconstruction of the Holocene palaeoenvironmental evolution in the central São Paulo State (Brazil) based on anthracological analyses, in association with soil isotopic composition (δ13C) and radiocarbon dating from four sites. Anatomical identification of charcoal particles allows the reconstitution of past plant associations, and consequently of the vegetation and climate history. Rather precise interpretations may be achieved when associating anthracology and soil δ13C analysis. In the early Holocene, climate was dry and an open cerrado vegetation (savanna) covered most of this area. A cerradão (forested savanna) or a semideciduous forest existed in the more humid localities. After 3500/3000 14C yr BP the climate was more humid, similar to the present, leading to the establishment of forested vegetation in all the studied sites. Com parison of these results with various palaeoenvironmental studies carried out in the Brazilian phytogeographical zone of cerrado and semideciduous forest suggests that at least its greater part presented a similar trend in the climatic evolution during the Holocene. This phytogeographical zone presented a dry climate during the early Holocene, then a more humid climate during the late Holocene. Climatic conditions similar to the present appeared from 5000 to 1000 yr BP, depending on the site.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".