Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The drift of the resistance of sensors used in thermal (such as hot-wire and hot-film) anemometry remains a perpetual concern for users of constant-temperature anemometers (CTAs). Even small changes in the resistance of such sensors result in error if the sensor was calibrated prior to the occurrence of the drift. In the present work, modified forms of the relationship between the output voltage of a constant-temperature anemometer and the fluid velocity, which take into account the sensor resistance as well as other resistances involved in the Wheatstone bridge (top resistance, operating resistance, cable and probe resistances), are used to minimize the sensitivity of the CTA to changes in the sensor resistance. These new relationships are tested using (i) two different CTAs and (ii) three hot-wires of differing resistances (3– ), and are shown to collapse the calibration data, even though the sensor resistances had drifted. It is expected that use of this method would reduce the frequency of calibrations needed to maintain satisfactory degrees of accuracy and repeatability in experimental measurements of fluid flows made using CTAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it