Genetic variation in three North American barn owl (Tyto alba) populations using DNA fingerprinting
Bibliographic record
Abstract
I studied the genetic diversity of a small population of common barn owls (Tyto alba) in British Columbia (BC), Canada. DNA fingerprinting was employed to assess the level of genetic variation in the BC population compared to two other barn owl populations in North America, California and Utah. Two different multilocus probes, Jeffreys' 33.15 and per, were used with the restriction enzyme Haelll. These probes yielded sufficient variation at minisatellite loci to assess the general level of relatedness both within and between populations. The number of scorable bands on each fingerprint was significantly higher when probed with per than when probed with Jeffreys' 33.15, but both probes resulted in similar band sharing patterns, and neither showed any apparent linkage. Band sharing between each pair of individuals on a gel was calculated as In^Kjif^ + nB),' where nA and wB are the number of bands in the fingerprints of individuals A and B, and nA B is the number of bands shared by A and B. Band sharing coefficients were significantly higher in the BC barn owl population than in the California or the Utah populations, indicating less genetic variation in the BC population compared to the other two. Between population band sharing was highest between Utah and California, reflecting more genetic similarity between those two populations. The results indicated that the genetic variation in the BC population is still within the range of other viable populations. Levels of organochlorine and PCB residues in barn owl livers also have dropped consistently since 1975 (Appendix 1). To conserve Canada's barn owls, it will be important to continue monitoring genetic variation in the BC population and to maintain barn owl habitat in the Fraser Valley.
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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 | 0.000 |
| 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 | 0.000 |
| 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".