Freezing Rain Simulations for Fixed, Unheated Conductor Samples
Why this work is in the frame
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Bibliographic record
Abstract
The present paper reports on extensive experiments performed on short, fixed, unheated conductor samples in an outdoor freezing rain simulator. Their purpose is to relate the weight of ice (or, alternatively, the equivalent radial ice thickness) accreted on the samples with the associated weather conditions. Over 50 specimens have been obtained under environmental conditions that encompass both wet and dry ice growths as well as several wind conditions. A nondimensionalization technique is devised to accommodate variations in the imperfectly controlled test conditions. Consistent experimental results could be discerned more clearly when the horizontal as well as the vertical precipitation rate were measured. A strong linear correlation is found between a dimensionless ice thickness and a dimensionless time. A simple model, Goodwin’s model, is found to fit the experimental data surprisingly well for both dry and wet ice growths.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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