A Composite Bridge is Favoured by Quantifying Ecological Impact
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
Carrying traffic loads is not the only objective of bridge designers nowadays. Other demands include constructing a bridge in a sustainable way, which reduces pollution and other harm to the environment. In The Netherlands, the government responds to such demands by promoting technologies and materials that decrease the environmental impact of construction projects. An assessment of that impact is, however, quite complex for bridge projects. The existing analytical methods, such as life-cycle analysis (LCA), require an extensive data input. Moreover, their results are more reliable for relatively simple products of short life cycles, for example, door or window frames, than for complex construction projects. In construction projects, the life cycles cannot be determined with the same precision and the materials are usually chosen in the very early stage of design. As a result, the data required by the LCA are often incomplete or even disputable. Therefore, there is a demand for ecological analysis methods that enable quick scanning of several material options, require less-extensive data input and are hardly, or not, vulnerable to arbitrariness.
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 | 0.000 |
| 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 it