Technical Note: An Algorithm for the Detection of Steady-State Measurements of Gas Emissions From Compost
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
High concentrations of carbon monoxide (CO) have been observed in the enclosed composting facility at the Edmonton Waste Management Centre in Alberta, Canada. An elevated concentration of CO in the facility is a potential health threat to workers. Research was conducted to assess the temporal and spatial variability of CO emissions from the composting bays, using Fourier Transform Infrared spectroscopy. Repeated gas measurements of CO, CO2, and CH4 were taken above and inside the compost bed using a metal gas probe. The probe was connected to the FTIR gas analyzer, which continuously collected gas concentration data. The data collected using the FTIR resulted in a continuous time series of gas measurements, where the peaks in the data signal corresponded to gas measurements taken inside the compost, and valleys represented the gas measurements taken above the compost bed. This article describes the algorithm that was devised to determine the gas concentrations at each sampling location using the MATLAB programming environment. The algorithm was able to successfully identify the sampling locations from the continuous gas measurement data, and determine the average steady-state gas concentration above and inside of the composting bays for CO, CO2, and CH4.
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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