Bibliographic record
Abstract
Experiments involving a magneto-optical trap (MOT) as the target in electron impact cross section studies were carried out. The use of a MOT allows the kinematic properties of the target atoms, and their electronic states, to be controlled via operating parameters of the MOT's lasers. A MOT is capable of saturating the excited state of a gaseous target of atoms and provides a unique opportunity to measure exotic collision processes. Measurements use a trap-loss technique to relate the loss rate of atoms from the trap due to electron interactions to a collision cross section. Total scattering cross section measurements are given for the 62S 1/2 ground state and the 62P3/2 excited state of cesium. The excited state measurement is the first measurement of its kind. Total ionization cross sections are also presented for the both the 6 2S1/2 ground state and 62P3/2 excited state. The ionization cross sections are measured by adjusting the radiation force of the MOT lasers to damp the elastic scattering component of the total cross section. The ionization cross section for the excited state is the first experimental determination of its kind. Full details of the experimental apparatus and the analysis procedure are presented. The results of this experiment are combined with other experimental data and compared to the most recent calculations.Dept. of Physics. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .M322. Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 4996. Adviser: J. W. McConkey. Thesis (Ph.D.)--University of Windsor (Canada), 2003.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".