Assessing the methane mitigation potential of Canadian red seaweeds using in vitro batch culture
Bibliographic record
Abstract
Seven red Canadian seaweeds ( Callophyllis flabellulata, Graciliariopsis verrucosa, Mastocarpus papillatus, Mazzaella splendens, Mazzaella japonica, Palmaria mollis, and Prionitis lanceolata) and a positive control ( Asparagopsis taxiformis) were selected to evaluate their chemical and elemental composition and their effects on in vitro fermentation and methane (CH4) production in an alfalfa hay or barley straw diet. The in vitro batch culture was conducted as a completely randomised design with a control (alfalfa hay or barley straw) and seven increasing concentrations of seaweed. Chemical and elemental composition varied greatly across seaweed genera. Increasing supplementation of A. taxiformis linearly decreased ( P < 0.001) dry matter disappearance (DMD) and gas production (GP; mL, mL/g DMD) with CH4 production eliminated ( P < 0.001) at 1.0% inclusion of A. taxiformis in both diets. Inclusion of Mastocarpus papillatus, Mazzaella japonica, Mazzaella splendens, Palmaria mollis, and Prionitis lanceolata increased ( P ≤ 0.05) GP (mL/g DMD) at 0.5% and 1.0% in alfalfa diets. Graciliariopsis verrucosa linearly decreased ( P = 0.01) CH4 production (mL/g DMD) in the straw diet, but no doses were different compared to the control. In conclusion, the Canadian red seaweeds examined in this study did not exhibit anti-methanogenic potential when incubated with alfalfa hay or barley straw.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".