Quantification of anaerobic digestion feedstocks for a regional bioeconomy
Bibliographic record
Abstract
Anaerobic digestion (AD) for biogas production forms one of the fundamental building blocks of the bioeconomy, and a research programme has been under way in Northern Ireland, which culminated in the publication of a Biogas Research Action Plan 2020 in 2014. One important element of this programme was the identification of the need for an evidence base for the potential bioresource feedstocks. This paper reports the outputs of the quantification of feedstocks for AD research, which has identified the organic feedstocks available for biogas production on a regional basis and categorised these as: organic (biodegradable) fraction of municipal solid waste, sewage sludge, organic industrial and commercial wastes, manure from livestock, food wastes and energy crops. The research study further quantified the biogas and energy potential of these feedstocks and possible reductions in greenhouse gas emissions. The limitations of the research study are acknowledged and opportunities to address these and build on and extend the study are identified, including feedstocks for other bioeconomy processes and the application and further development of the biorefinery concept.
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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 | 0.000 |
| 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 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".