Potential distribution of the endangered endemic lizard Liolaemus lutzae Mertens, 1938 (Liolaemidae): are there other suitable areas for a geographically restricted species?
Bibliographic record
Abstract
In this study we attempted to access further information on the geographical distribution of the endangered lizard Liolaemus lutzae, estimating its potential distribution through the maximum entropy algorithm. For this purpose, we related its points of occurrence with matrices of environmental variables. After examining the correlation between environmental matrices, we selected 10 for model construction. The main variables influencing the current geographic distribution of L. lutzae were the diurnal temperature range and altitude. The species endemism seemed to be a consequence of a reduction of the original distribution area. Alternatively, the resulting model may reflect the geographic distribution of an ancestral lineage, since the model selected areas of occurrence of the two other species of Liolaemus from Brazil (L. arambarensis and L. occipitalis), all living in sand dune habitats and having psamophilic habits. Due to the high loss rate of habitat occupied by the species, the conservation and recovery of the remaining areas affected by human actions is essential.
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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 | 0.000 | 0.001 |
| 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".