Identification and evaluation of VOCs evolved from warm season swine mortality composts
Bibliographic record
Abstract
The intensive production of swine in Iowa (28.4 % of the U.S.A production) inevitably results in high amounts of piggery waste including animal carcasses. Composting is an environmentally sound and relatively inexpensive method to dispose swine mortalities especially when the carcasses are diseased. Measurement of VOC emissions is an alternative to test progress and completion of the process. In this study, diseased swine mortalities are composted in summer conditions of Central Iowa. Corn silage, oat straw and corn stalks are used as envelope materials. Once a week, air samples are collected from the center of test units and sampled with 85 µm Carboxen/ polydimethylsiloxane (CAR/PDMS) solid phase microextraction (SPME) fiber. Samples were analyzed using gas chromatography (GC) - mass spectrometry (MS). The objective of the study is to investigate the potential usage of VOCs as indicators of swine mortality degradation. It is found that nitrogen and sulfur containing compounds can be used as indicators of the composting process. Sulfur-containing compounds are detected from all test units. Nitrogen-containing compounds are detected from only corn silage test units. It is concluded that carcass degradation is incomplete in all of the test units. Carcass degradation in corn stalks and oat straw test units is better than corn silage test units. These results are supported with respiration rate results. Respiration rates of the remaining swine carcasses are found to be between 5-7 mg CO2-C g VS-1d-1 and swine carcasses are categorized as moderately unstable composts.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".