Bibliographic record
Abstract
Cliffs worldwide support a variety of protists and animals including a vast array of invertebrates, amphibians, reptiles, birds and mammals. Cliffs in one area of highland in southern British Columbia, Canada, for example, supported 41 per cent (22 of 54) of the faunal species of high conservation value for the region (Sinnemann, 1992). Most studies of cliff fauna, however, have focused on one or a small number of species. This is in striking contrast to the floristic studies reviewed in the last chapter that generally focused on the determination of the composition of the entire plant community. In most faunal studies, the focus of the research is usually not on the habitat but rather directly on the species that occur there. Exceptions to this trend in the faunal literature include Johnson (1986), Reitan (1986), Ward and Anderson (1988), and Camp and Knight (1997). As a result, the organization of this chapter is quite different from the preceding one. This chapter summarizes the information that is presently available in the scientific literature on the ecology and distribution of faunal cliff species and presents it in broad taxonomic groups. Avifauna General trends Cliffs appear to support a greater species richness of birds than equal areas within the surrounding habitat, although not all of these birds nest on the cliffs. This difference between adjacent land and cliffs is partly attributable to cliffs being ‘permanent habitat edges’ characterized by abrupt changes in soil, topography, geomorphology and microclimate combined with local conditions that minimize interspecific competition and predation (Matheson & Larson, 1998).
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.149 | 0.045 |
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".