Bibliographic record
Abstract
In the summer of 1993, a group at TRIUMF commissioned the Canadian High Acceptance Orbit Spectrometer (CHAOS). This is a 360° spectrometer that was built to study Π[sup ±]p elastic scattering and the (Π, 2 Π) reaction in order to investigate the possible effects of chiral symmetry in QCD. An important part of the vast readout electronics is the second level trigger, which performs several fast calculations in hardware to determine the merit of an event before writing it to tape. The trigger performs various cuts on single outgoing tracks: momentum, polarity, distance of closest approach to the origin of CHAOS, and momentum versus scattering angle. In addition, the trigger can look for two such acceptable tracks and then perform cuts based on the sum of the momenta and the comparison of the polarities; this section in particular is crucial for the success of the (Π, 2 Π) program. Finally, the second level trigger can survey the incoming beam and reject events in which an incident pion decayed to a muon before reaching the CHAOS target. This thesis will first provide an introduction to the theoretical motivation behind CHAOS and also outline the various components of the spectrometer in brief. The remainder of the thesis will discuss in detail the purpose and operation of the different sections of the second level trigger.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".