Using a Modified Failure Modes and Effects Analysis Within the Structured Design Recovery Framework
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
Design recovery is defined as determining the relevant form and functions and their relationships for a component in order to generate a complete engineering representation. To lead to a more complete model, an integrated approach that assesses the component from different perspectives is presented here, as no one perspective or set of tools can provide a comprehensive engineering representation. There is always the potential for error; hence, the necessity to assess latent design and/or design recovery issues in rigorous manner. A modified failure modes and effects analysis (FMEA) was developed to provide a foundation for the reconstructed model’s design validation. The modified FMEA is designed to interface directly with the design recovery framework. A matrix based procedure, which considers feature functions and relationships, is developed to assist the designer to quickly assess the feature design using a consistent structured approach. The results are plotted, and subsequent testing strategies are suggested based on the characteristics of the features being assessed. Examples illustrate the proposed methodologies and highlight their merits.
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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