An Integrated Systematic 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
Abstract Reverse engineering aims at reproducing an existing object by analyzing its dimensions, features, form, and properties. Reversing geometry has traditionally been emphasized in this process. The collected data and information must be transformed into pertinent product knowledge at both the detail and embodiment levels. A thorough analysis of the environment must be conducted in order determine the functional requirements, infer the original needs, and deduce the form and fit features. An integrated approach that blends techniques such as IDEF modeling, scanning, and physical measurements, least-squares methods, and statistics used for process capability analysis in an innovative manner can lead to a more complete model, as no one set of tools can provide a complete, comprehensive engineering representation. An integrated and systematic framework for design recovery of mechanical parts is proposed. Forward engineering techniques should be applied appropriately throughout and integrated with the reverse engineering process to heal the knowledge gaps. Examples are presented that illustrate the application of the proposed integrated approach and highlight its merits.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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