Evidence for Cryptic Genetic Discontinuity in a Recently Expanded Sika Deer Population on the Boso Peninsula, Central Japan
Bibliographic record
Abstract
The genetic structure of populations is not necessarily reflected in the geographical proximity of individuals, because environmental gradients such as those of vegetation or climate can function as cryptic barriers to gene flow. We examined polymorphisms at nine microsatellite loci to determine and discuss whether a distinctive genetic structure was detectable in a spatially continuous population of the sika deer (Cervus nippon) on the Boso Peninsula of central Japan. Spatially explicit Bayesian analysis revealed that two genetically distinctive clusters exist in the Boso population. The spatial boundary of the two clusters approximately conformed to the border defined previously from a mitochondrial DNA dataset. By combining information on the geomorphic features surrounding the boundary and that on the lineage of 1970s population, we propose a schematic scenario for characterizing the population genetic structure to the present. The current population consists of genetically different lineages, and spatially discontinuous clusters have come into contact in the vicinity of a local road running along a steep-walled ravine that could act as principal barrier to gene flow. Biological factors such as distribution of vegetation and philopatric behavior might also have helped strengthen the cryptic genetic structure of the Boso population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".