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 dissertation discusses the construction and use of a new design tool, the Axiomatic House of Quality (AHOQ). Many organizations have experienced problems with the implementation of the current House of Quality (HOQ) model. Problems included excessive development time, costs, and the loss of the customer's requirements. The author believed that the cause of these problems was due to differences in format, and misunderstanding of HOQ terminology. The author assumed that a standard model and terminology would reduce confusion during development and expedite the design process. However, most problems with the HOQ resulted from customer requirement dependencies. These dependencies cause excessive time as design teams attempt to resolve conflicting requirements. It was concluded that a standard model and terminology would not significantly improve the HOQ. Instead, principles and methods of the HOQ would be examined and modified to correct problems with consumer requirement dependencies. This dissertation discusses the need for changes in the principles and methods used in the HOQ. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .M36. Source: Masters Abstracts International, Volume: 40-03, page: 0765. Adviser: Filippo Salustri. Thesis (M.A.Sc.)--University of Windsor (Canada), 2001.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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