Pronghorn habitat suitability in the Texas Panhandle
Bibliographic record
Abstract
ABSTRACT Habitat quality is an important factor that can greatly affect wildlife populations. Pronghorn (Antilocapra americana) habitat in the Texas Panhandle, USA has been lost through growth of human settlements and agricultural lands. We determined the most pertinent environmental variables affecting habitat selection using multiple methods, including a search of peer‐reviewed literature, expert opinion ranking, and habitat suitability modeling. We determined quality and extent of pronghorn habitat in the Texas Panhandle using the MAXENT modeling environment to build a presence‐only habitat suitability model based on global positioning system (GPS) locations collected via aerial surveys. Our habitat suitability model indicated that woodlands, agricultural land, and summer precipitation had the greatest contributions to the overall model. Areas with greatest habitat suitability are associated with high pronghorn population densities, particularly in the northwestern corner of the Panhandle. This probabilistic model may serve as a useful tool for pronghorn conservation primarily because it provides insight into what factors are most predictive of their presence, which areas are most suitable for pronghorn, and as a simple, replicable process to identify and evaluate pronghorn habitat. © 2016 The Wildlife Society.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".