What's new with FASTBUS and what's it done in the particle accelerator laboratories
Bibliographic record
Abstract
Implementations of FASTBUS have been made in accelerator laboratories worldwide, resulting in clarifications, modifications and extensions of the specifications. Of tremendous benefit to users have been FASTBUS Standard Routines. The availability of such standard software is unique for high-speed bus systems and resulted from the involvement of hardware and software specialists in all aspects of the development. FASTBUS is the highest-performance instrumentation and data acquisition bus in existence and its development was essential to handle the outputs of detectors used with high-energy accelerators now in operation. It has been an important factor in experiments, including the Z/sup 0/ measurements at CERN, Fermilab, and SLAC (Stanford Linear Accelerator Center). Also among numerous FASTBUS implementations are those for TPC (TOPAZ Time Projection) systems at KEK (Japan National Laboratory for High Energy Physics) and BNL (Brookhaven National Laboratory).>
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.014 | 0.042 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.031 |
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".