Bibliographic record
Abstract
PMTs, and restores the time resolution to the extent possible. The PMT calibration also converts the integrated charge into the same units for all PMTs. This thesis describes how the PMT calibration is implemented and presents the results of investigations into its performance. The PMT calibration is found to perform well and is crucial to the analysis of SNO data. The Sudbury Neutrino Observatory (SNO) is a solar neutrino experiment designed to search for neutrino flavour oscillations. It is located 2040m underground in the INCO, Ltd. Creighton mine near Sudbury, Ontario. The detector consists of a kilotonne of heavy water (D sub 2 O) viewed by approximately 9,500 Photomultiplier Tubes (PMTs). The PMTs detect Cerenkov photons produced following the interactions of sup 8 B solar neutrinos with the D sub 2 O. These neutrinos can interact with D sub 2 O in three different ways. This allows the electron neutrino flux and the total flux of all flavours of neutrino to be measured. In order to distinguish the different types of reaction, it is essential to reconstruct where the interactions took place in the detector. The reconstruction critically depends on an accurate knowledge of the relative times at which the PMTs detect the Cerenkov photons. The first results from SNO provide strong evidence for neutrino oscillations and have further constrained the possible values of the square of the neutrino mass differences and the neutrino mixing angles. The topic of this thesis is the Photomultiplier Tube Calibration. The SNO electronics record a time and an integrated charge for each PMT that is triggered by a photon. The recorded time has an unknown offset and the time resolution of the PMTs is degraded by an effect arising from variations in the pulse sizes. The PMT calibration removes the time offsets, giving the relative timing of the
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".