Bibliographic record
Abstract
Testing the degree of support for macroecological patterns requires that the data behind these hypotheses be available for examination and re‐testing. Using geographically wide‐spread incidence matrices and a multi‐gene phylogeny for ants (Hymenoptera: Formicidae), I calculated phylogenetic measurements of alpha and beta diversity and elevation to test the degree of support for the expected relationships between diversity and elevation (negative) and between phylogenetic clustering and elevation (positive). Whether diversity was estimated morphologically or phylogenetically, the elevational decay of alpha diversity was more frequently a linear decline than a mid‐elevation peak. However the expectation that phylogenetic community structure would more likely be clustered with increasing elevation was not supported. This might be due to the fact that the physiological limitations filtering the taxa present are expressed at the species level and are thus beyond the resolution of this phylogeny. Trends linking elevational decay in beta diversity to temperature and precipitation were weak, but the results do support Janzen's 1967 prediction that communities on tropical mountains were less similar to each other than in temperate mountain communities. At the genus level, these data suggest that there is no general pattern regarding whether environmental/habitat filters (clustering) or inter‐specific competition (dispersion) filter the taxa present. Instead, this analysis suggests that the community assemblages are not significantly different from random across elevation or temperature. These findings reinforce how important it is to support intuition with data and how critical it is to make data public and accessible so that hypotheses can be re‐examined and tested.
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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".