Population Variation Revealed High-Altitude Adaptation of Tibetan Mastiffs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the assistance of their human companions, dogs have dispersed into new environments during the expansion of human civilization. Tibetan Mastiff (TM), a native of the Tibetan Plateau, was derived from the domesticated Chinese native dog and, like Tibetans, has adapted to the extreme environment of high altitude. Here, we genotyped genome-wide single-nucleotide polymorphisms (SNPs) from 32 TMs and compared them with SNPs from 20 Chinese native dogs and 14 gray wolves (Canis lupus). We identified 16 genes with signals of positive selection in the TM, with 12 of these candidate genes associated with functions that have roles in adaptation to high-altitude adaptation, such as EPAS1, SIRT7, PLXNA4, and MAFG that have roles in responses to hypoxia. This study provides important information on the genetic diversity of the TM and potential mechanisms for adaptation to hypoxia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it