Bibliographic record
Abstract
Remington (1968) argued that 13 suture zones exist in North America. Remington defined a suture zone as, "a band of geographic overlap between major biotic assemblages, including some pairs of species or semispecies which hybridize in the zone" (p. 322). Although initially controversial, the idea that suture zones exist has picked up momentum over the past decade, due largely to the phylogeographic work of Hewitt, Avise, and their colleagues. Nevertheless, the reality of suture zones has not yet been subjected to rigorous analysis using statistical and geographic information system (GIS) approaches. To test for the existence of Remington's suture zones, we first identified 117 terrestrial hybrid zones in Canada and the United States through a literature search for the key words "cline," "contact zone," "hybrid zone," and "hybridization" in articles published between 1970 and 2002. The 117 hybrid zones were mapped using a GIS approach and compared with a digitized version of Remington's original suture zone map. Overall, there does appear to be an association between hybrid zones and suture zones, but this association is largely attributable to clustering of hybrid zones in only two of the 13 suture zones recognized by Remington. The results suggest that evolutionary biologists should retain some skepticism toward Remington's suture zones.
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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".