Bibliographic record
Abstract
The vertical orientation of cliffs represents the primary (if obvious) difference from other landscape types, but verticality affects the environmental conditions on cliffs in a number of important ways that are not always obvious to ecologists who study the microclimate of level ground or slopes. The function of this chapter is to point out the various ways in which the physical environment of cliffs is distinct from that of horizontal surfaces. Its purpose, therefore, is not to give a complete account of all components of the physical environment. The reader is referred to standard texts, such as Monteith and Unsworth (1990), Arya (1988), Oke (1987) and Gates and Schmerl (1975), for basic information on microclimate and energy balance. The first subsection briefly outlines the various components of the physical environment that are affected by vertical orientation of the substrate, and shows how these factors are interconnected in a complex way to make the cliff environment drastically different from surrounding level ground. More detail on each of these factors is then provided in the subsections that follow. The effects of vertical orientation Vertical orientation affects the total amount of direct radiation a surface receives and the way radiation input varies diurnally, seasonally and latitudinally. It also affects wind speeds on the surface and the amount of direct precipitation received. Radiation, wind and moisture together control the temperature of the rock. Absorption of radiant energy increases rock temperature, while wind speed controls the amount of energy that is dissipated by the heating of air and the evaporation of moisture, thus cooling the cliff surface.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.105 | 0.039 |
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".