Bibliographic record
Abstract
Two Sentry SVS-1 visibility sensors were installed at the Iqaluit Weather Office site. One instrument was an RS-232 Output version (Visibility 1), while the second was Analog version (Visibility 2) of the instrument. The instruments had measurement ranges of 30 m to 16 km with an accuracy of ± 10%. Both sensors were set to sample once every minute, and mounted at a height or 1.5 m. Visibility 1 (RS-232 output) was positioned on the east side of the Upper Air shed at the Weather Office during the fall field campaign. The data files were logged using an Acumen Data Logger, and stored on a compact flash card. Data files are in *.dat format where they contain date, time, sensor output voltage (VDC), visibility in (km). To derive the visibility from the VDC the following formula was used: σ km-1 = 20* (0.150/VDC). Visibility 2 (Analog output), was positioned with the 10-m tower automatic weather station (A3) and the Weather Office site. A Campbell Scientific CR23X data logger was used to log the data. Data files are in a simple *.csv format where they contain date, time, visibility (km). To derive the visibility from the VDC the following formula was used: σ km-1 = 20* (0.150/VDC). Data from this instrument was downloaded daily during the Fall period and weekly during the winter period. This was accomplished by exchanging the CF card in the data logger. The CF card was then brought into the Environment Canada weather office, where it was offloaded onto the STAR desktop computer. To exchange the CF cards, the data logger had to be turned off for periods between 1-5 minutes. As a result, 1-5 minutes of data is missing during these time periods. This instrument moved over to the 10-m tower weather station (A3) for the winter blowing snow project (Feb 1- March 30). The same downloading procedure was adpated , however downloads occurred on a weekly basis. See Visibility 1 Winter metadata form for more info.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.088 | 0.073 |
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".