Bibliographic record
Abstract
Palaeo-ecological modeling is an important part of palaeoanthropology because major habitat changes are associated with significant evolutionary changes.To be able to derive an understanding of as to why Homo ergaster succeeded Homo habilis, Homo rudolfensis, and Paranthropus boisei we must understand the environmental factors that would have contributed to the evolutionary success of H. ergaster.In the analyses of extant and extinct fauna and flora from the Plio-Pleistocene and the microwear on hominid tooth remains we can develop an idea of what ecological niches these hominids may have exploited.However, what remains to be uncovered is how they were able to exist sympatrically with such evident dietary overlap.It is thus of utmost importance for palaeoanthropologists and primatologists to collaborate information in order to develop analogies between fossil hominids and extant primates.Potential analogies can be explored between gorillas, chimpanzees, bamboo lemurs and early hominids.Such analogies will aid in the reconstruction of Plio-Pleistocene environments that allow us to answer regarding whether ecological factors influenced initial hominid diversity and eventual extinction.Madagascar.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".