Computer Application to Study Engineering Projects at the Early Stages of Development
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 describes a computer software application, the Qualitative Engineering System (QES), which the engineer can use to perform qualitative and semi-quantitative analysis of preliminary engineering designs. In engineering practice, many situations arise in which the engineer wishes to perform a logical, objective comparison between conceptual or preliminary design options. Although there exist many applications which can be used to perform detailed numerical analysis to justify detailed final designs, relatively fewuseful programs are available to validate designs at the preliminary stages. The early stages of design are characterized by higher levels of uncertainty than the latter stages. Established qualitative and semiquantitative reasoning techniques may be used to detail with uncertainty and incomplete information in a sound, logical manner. The QES application utilizes a unified framework, which is used to implement a number of qualitative and semi-quantitative reasoning techniques. This paper gives an explanation of qualitative and semi-quantitative analysis in the context of the QES application. In addition, the paper gives some practical examples of how the QES program can be used in the engineering 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 | 0.001 | 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) | 0.000 | 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