Performance testing of wildland fire chemicals using a custom-built heat flux sensor
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
A simple and effective laboratory test methodology was developed for differentiating wildland fire chemicals based on the ignition time of vegetative fuel samples. The test apparatus consisted of an electric-powered radiant heater that was used to produce a uniform radiant thermal load to ignite the vegetative fuel samples. The samples, treated with wildland fire chemicals, were mounted on to a load cell to determine the transient mass loss during the combustion process. A custom-built heat flux sensor, that was modified and tested to reduce high errors, was used to determine the time to flaming ignition. The time to flaming ignition was also measured using transient mass loss data of the vegetative fuel samples. Statistical t-test analysis was conducted on the time to flaming ignition to determine whether the results were statistically significant for the different chemical treatments. The results indicated that the test methodology allowed for effective differentiation between the wildland fire chemical treatments by comparing their mean ignition times. The narrow standard deviations of the average ignition times suggested that the test methodology was able to produce repeatable results.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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