Bibliographic record
Abstract
TREX (21 cm Reionization EXperiment/Trail Reflection EXperiment) is a digital spectrometer with a broadband antenna optimized for frequencies of 70–250 MHz. A frequency-independent rectangular approximation of a two arm conical spiral antenna has been designed, built and tested. I have developed a short integer fast Fourier transform which performs faster than any other known algorithm on Intel platforms. There are two primary scientific goals for TREX: detection of the reionization epoch, and observations of forward scattering of meteors at multiple frequencies. A method to detect the reionization signature via the red-shifted 21 cm hydrogen line is discussed in detail. If the spectrum signature due to this line is in the form of a sharp "temperature step" of ∼ 0.02 K, it should be possible to detect it by using two specially designed antennas each rescaled by 1% in the frequency range of 150-250 MHz. I have measured the levels of noise in Algonquin Park, Canada, and concluded that activity in the sporadic E layer of the ionosphere seriously affects observations of the 21 cm reionization signature. Meteor forward-scattering is a well known method of detecting meteors using a radio telescope to receive signals emitted by distant transmitters and scattered from a meteor trail. If the same meteoroid is detected at additional frequencies due to forward scattering of rays coming from spatially separated transmitters, it is possible to estimate where the scattering occurred, and find the meteoroid velocity vector. Previously, there were no known methods to estimate orbital parameters from forward-scattering observations. In this project, a pipeline to find orbital parameters from the observations is developed. I performed a set of meteor observations at the Algonquin Radio Telescope site and used data to demonstrate the method of measuring the speed of a meteoroid. The data gathered show increased activity during the Lyrid meteor shower as expected. Finally, no evidence was found for the Pegasid shower.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 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".