Bibliographic record
Abstract
Species diversity patterns of high elevation grassland Diptera (Brachycera) were assessed to determine the community structure, species turnover, and species abundance patterns along a latitudinal gradient. Fieldwork took place in May 2008 in the Appalachian Mountains of North Carolina and June-July 2010 in the Rocky Mountains at sites in Colorado, Wyoming, and Alberta. Two spatial scales were used: sample area and site. There was a slight latitudinal turnover of species, with latitude, longitude, and elevation being the most strongly associated with species composition. All sites were significantly different except the two sites in Alberta. Close proximity and site similarity may be responsible for this. There were similarities between all sample areas except Colorado. These results are attributed to the Wyoming basin, possibly a considerable barrier to dispersal. Patterns were driven mostly by rare species. High beta-diversity was found between sites, even in patterns of common species. Species abundance patterns in both the Rockies and the Appalachians revealed that although ecologically diverse and broad generalist families were more reliably dominated by a few species, trophic guild may not always accurately predict dominance/evenness patterns.
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 | 0.000 | 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) | 0.001 | 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".