Ribosomal DNA variation in the grasshopper,<i>Dichroplus elongatus</i>
Bibliographic record
Abstract
We report an RFLP analysis of ribosomal DNA variation in natural populations of the grasshopper, Dichroplus elongatus, previously analyzed for mitochondrial DNA variation. DNA samples were digested with five restriction enzymes, BamHI, EcoRI, HindIII, PstI, and XbaI. BamHI was the only enzyme that showed no variation. The remaining enzymes showed fragment size variation at both intra- and interpopulation levels. Stepwise regression analysis revealed that the average number of length variants per individual is significantly associated with altitude. Moreover, the same analysis indicated that the frequency of some restriction variants exhibits a significant regression on both geographic and climatic variables. The intra- and interpopulation variability of rDNA was analysed by Lynch's and Hedrick's similarity indices using presence or absence of a fragment and band intensities, respectively. The corresponding neighbour-joining (N-J) trees based on Lynch's and Hedrick's genetic distances resulted in similar topologies. However, these trees were not in agreement with the N-J dendrogram obtained from mtDNA data previously reported by Clemente et al. (2000). The disagreement between mtDNA and rDNA phenograms along with the observed correlation between rDNA variability and geographical and climatic variables suggest some form of selection, besides genetic drift and migration, is involved in the pattern of rDNA variation.
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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 | 0.000 | 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 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".