Nested patterns of beta-diversity in forest Diptera
Bibliographic record
Abstract
Nested patterns of diversity in temperate forest Diptera (Schizophora) were assessed, to determine the scale contributing the most to fly diversity in this habitat. Fieldwork was carried out in June-July 2008 in three southwestern Quebec forest fragments, using three spatial scales (tree, stand, and site). Diptera species diversity (239 species) and composition was non-random at all scales selected. These scales did not contribute equally across the different groups, as shown by different diversity patterns. Smaller scales seem to structure Diptera species composition (beta1: between trees), as well as the two major taxonomic subgroups (Calyptratae and Acalyptratae). Common species were also more important at finer scales (alpha1: within trees), while rare species varied more at broader scales (beta3: between sites). The scale contributing the most to γ-diversity was variable across the different groups, although beta1 was generally strongest. Environmental variables supported species composition only weakly.
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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 | 0.001 |
| 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) | 0.002 | 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".