Data from: Phylogeography and population history of Leopardus guigna, the smallest American felid
Bibliographic record
Abstract
The guigna (Leopardus guigna) is the smallest and most-restricted New World cat species, inhabiting only around 160,000 km2 of temperate rain forests in southern South America and is currently threatened by habitat loss, fragmentation and human persecution. We investigated phylogeographic patterns of genetic diversity, demographic history and barriers to gene flow with 116 individuals sampled across the species geographic range by analyzing 1,798 base pairs of the mtDNA (496 bp HVSI region, 720 bp NADH-5 gene, 364 bp from 16S gene and 218 bp from ATP-8 gene) and 15 microsatellite loci. Mitochondrial DNA data revealed a clear phylogeographic pattern with moderate separation between northern and southern Chilean populations supporting recognized subspecific partitions based on morphology. A recent demographic expansion was inferred for the southern-most group (San Rafael Lake), presumably due to the complete coverage of this area during the last glacial period, 28000–16000 years BP. Geographical barriers such as the Andes Mountains and the Chacao Channel have partially restricted historic and more-recent gene flow and the Chiloé Island population has diverged genetically since being separated from the mainland 7000 years BP. This is the first study of the genetic structure of this threatened species throughout its whole geographic range.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".