An Electronic Nose Network System for Online Monitoring of Livestock Farm Odors
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
An electronic nose (e-nose)-based network system is developed for monitoring odors in and around livestock farms remotely. This network is built from compact e-noses that are tailored to measure odor compounds and environmental conditions such as temperature, wind speed, and humidity. The e-noses are placed at various applicable locations in and around the farm, and the collected odor data are transmitted via wireless network to a computer server, where the data processing algorithms process and analyze the data. The developed e-nose network system enables more effective odor management capabilities for more efficient operation of odor control practice by providing consistent, comprehensive, real-time data about the environment and odor profile in and around the livestock farms. Experimental and simulation results demonstrate the effectiveness of the developed system.
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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 | 0.001 |
| 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