Effects of vertical green technology on building surface temperature
Bibliographic record
Abstract
The International Journal of Design & Nature and Ecodynamics acts as a forum for researchers from around the world working on a variety of studies involving nature and its significance to modern scientific thought and design.Throughout history, many leading thinkers have been inspired by the parallels between nature and human design.Today, the huge increase in biological knowledge and developments in design and systems, together with the virtual revolution in computer power and simulation modelling have all made possible more comprehensive studies of nature.Scientists now have at their disposable a vast array of relationships resulting in laws that have been assembled by observation and analysis, and span the cosmic scale of space down to the molecular level of genetics.In particular, they have demonstrated the rich diversity of the natural world.Ecodynamics aims to relate ecosystems to evolutionary thermodynamics in order to arrive at satisfactory solutions for sustainable development which is the most important challenge facing society today.It is the intention of the Journal to cover all aspects of ecosystems and sustainable development, ranging from physical sciences to economics and epistemiology.The International Journal of Design & Nature and Ecodynamics opens new avenues for understanding the relationship between arts and sciences.The objective of the Journal is to encourage and facilitate communication between scientists in different disciplines, as well as other professionals in academia, research institutions or industry, working on a variety of studies involving nature.
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 | 0.000 |
| 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) | 0.002 | 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".