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
Solar Architecture represents the confluence of the two disciplines of energy engineering and architecture. The concept of Solar Architecture defines a decision-making process to select, design, deploy, and operate solar energy-enabled solutions for environments where solar energy resources are part of the energy mix. The principles of Solar Architecture include maximizing solar energy harvesting from solution’s surfaces with a positive balance of energy, carbon, and cost provided by the solution. Solar Architecture application selection is built on two major cornerstones, features and groups, defining the best options in energy engineering of a solar solution. Solar surfaces are key to solar architecture. They are the “heart”, and balance-of-system components are the “muscles” of solar solutions. Addressing energy losses in photovoltaic, solar to thermal, and solar to chemical energy conversion allows for increasing energy harvesting yield. Life Cycle Assessment and solar energy harvesting methodologies based on solar surface characteristics define Solar Architecture Balance. This balance allows for defining energy, carbon, and cost return on investment for solar solutions and selecting the best solution for related assets/environment.
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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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