Characterization of NRC Convair-580 hot-wire probes performance using NRC AIWT
Bibliographic record
Abstract
This laboratory technical report presents the results of bulk cloud water content measurements taken with the Ice Crystal Detector and Nevzorov probes at the Altitude Icing Wind Tunnel of NRC. The Nevzorov and Ice Crystal Detector are aircraft-mounted hot-wire probes designed to find the bulk water content of clouds and are being used as the NRC Convair 580 aircraft core sensors. These two probes were tested in the NRC Altitude Icing Wind Tunnel facility in late 2020 and early 2021 in order to characterize their responsiveness to liquid water in a controlled environment. The probes were tested at a variety of liquid water content set points, particle median volume diameter, true air speed, pressure, and temperature. Measurements of the liquid water content and total water content were made in a setting of pure liquid conditions, and the probes measurements were compared to wind tunnel nominal values. The calculation of dry power loss for the Ice Crystal Detector was improved using a modified fit in the clear air. Icing was observed on both Nevzorov reference wires, creating a false signal and unreliable data, leading to the conclusion that the dry power loss should be calculated using the ambient parameters similar to how it is done for the Ice Crystal Detector.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".