Qualitative representation of trends: an alternative approach to process diagnosis and control
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
The potential for qualitative representation of trends in the context of process diagnosis and control is evaluated in this paper. The technique for qualitative description of the data series is relatively new to the field of process monitoring and diagnosis and is based on the cubic spline wavelet decomposition of the data. It is shown that the assessed qualitative description of trends can be coupled easily with existing process knowledge and does not demand the user to understand the underlying technique in detail, in contrast to, for instance, multivariate techniques in Statistical Process Control. The assessed links can be integrated straightforwardly into the framework of supervisory control systems by means of look-up tables, expert systems or case-based reasoning frameworks. This in turn allows the design of a supervisory control system leading to fully automated control actions. The technique is illustrated by an application to a pilot-scale SBR.
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 | 0.001 | 0.001 |
| 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