Integrating ecosystem theories – gradients and orientors as outcomes of self-organized processes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper discusses the ecological gradient principle and shows interrelations of this concept with several approaches of ecosystem analysis and theory. After a general description of ecosystem self-organization, ecological gradients are introduced as emergent ecosystem properties, their characteristics are explained, and different gradient types are distinguished. On this basis, the gradient principle is related to some other theoretical approaches of ecosystem comprehension: hierarchy theory, network theory, and thermodynamics. Thereafter, while observing ecosystem development, gradients are related to orientor theory, and the roles of disturbances are discussed. Few outcomes of the gradient principle for environmental management are listed, reaching from indicator derivation, integrity utilization to ecosystem service-based valuations. Finally, Bossel's basic orientor concept is used to show a gradient-related linkage between environmental and human systems.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it