Bibliographic record
Abstract
Millennium is a state-of-the-art system which has the following three targets as Paper Machine Control System: 1) Miniscule quality variations, 2) No sheet breaks, 3) Less than 2 minute grade changes. For example, measurement and control of cross-direction basis weight are to be explained hereafter.Basis weight control are limited by the following four items: 1) Profile measurement precision, 2) Measurement filtering time, 3) Process dead time, 4) Mapping.Improved basis weight profile control is as follows:1) The new Solid-state Silicon Technology (SST) basis weight sensor. This third-generation sensor uses a fast, high-efficiency silicon detector to measure basis weight instead of the high-noise ionization chamber used by conventional sensors.2) No filter is used for measuring. The correct data are measured instantaneously without time delay even at high scan speeds.3) Using the instantaneous data without filtering, process dead time is compensated correctly.4) The efficiency of CD control is improved with precise mapping between the zones of measurement and control.The improved control creates quality and financial benefits:1) Improved paper uniformity due to increased CD and MD profile stability, 2) Increased productivity and financial returns due to improved machine run ability and the ability to make faster grade changes.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.124 | 0.097 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".