<b>Densidad poblacional y ocupación del lince rojo (<i>Lynx rufus </i>Schreber)<i> </i>en el matorral espinoso</b>
Bibliographic record
Abstract
The bobcat (Lynx Rufus Schreber, 1777) is a mesopredator distributed from southern Canada to southern Mexico. Its presence is an indicator of good ecosystem quality. Although it is considered the most abundant felid in Mexico, there are very few studies that evaluate its population dynamics in arid zones. Therefore, the objective was to determine the population density and occupancy probability of bobcats in fragments of Tamaulipan thornscrub. Population abundance and density were estimated using camera traps and the MARK-CAPTURE tool. The vegetation composition of landscape corridors was evaluated to estimate their relationship with the bobcat population. An occupancy model was elaborated to analyze the presence of the species in the area, using environmental and anthropogenic impact covariates. The average density resulted in 8 individuals 100 km-2, derived from the identification of 23 bobcats and an effective sampling area of 140.31 km2. Sites 17 and 18 had the highest vegetation cover and the highest number of records, as well as a female with cubs and with different prey. The occupancy probability was positively associated with areas of higher vegetation cover. It is concluded that the density values presented are associated with the fragmentation of the vegetation community, and that the variables with the greatest influence on the presence of bobcats are vegetation cover and diversity.
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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) | 0.005 | 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".