1188 A novel method for collecting gas produced from the in vitro ANKOM gas production system
Bibliographic record
Abstract
Enteric methane produced by ruminants is a source of greenhouse gas emissions. One method for investigating methane production from ruminants is the in vitro method which when compared with in vivo methods is faster and less expensive. The ANKOMTM system is an in vitro system that periodically releases excess gas during the incubation to prevent it from diffusing into the medium. For this reason, a gas sample taken from the module's headspace at the conclusion of the incubation period may not be representative of the gas produced during the entire fermentation period. This study tested two methods that enable the collection of released gases. Yeast and sugar were incubated for 24 h in 310 mL ANKOMTM bottles equipped with an ANKOM module to regulate headspace pressure through ventilation. Incubations were made with three different methods: vented gas not collected (NC); vented gas collected in gas bags through a 304 cm gas sample line with an internal diameter (ID) of 1.0 mm (C304); and vented gas collected in gas bags through a 22 cm extension tube with an ID of 4.0 mm (C22). Each method was conducted using four different venting pressures (0.4, 0.6, 0.8, and 1.0 psi). When total gas production was calculated from absolute pressure measurements made by the pressure transducer in the ANKOM module, the mean of total gas production (ml) for the C304 method was significantly (P < 0.05) greater (125.3 ± 1.9) than either the C22 method (114 ± 1.9) or the NC method (115 ± 1.7), while the C22 method was not different from the NC method. There was no effect of venting pressure across treatments on estimated total gas production. It is concluded that the C22 method for collecting gas can be used in gas production studies with the ANKOM system as it does not interfere with measurement of gas production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".