Bibliographic record
Abstract
The urgently needed carbon neutral economy requires a portfolio of strategies, among which, CO2 capture and renewable energy will need to play a decisive role. Dispatchable renewables, such as bioenergy, will play an increasing role in maintaining electricity security, in producing heat in the industry and residential sectors, and in reducing the emissions from the transport sector. Biomethane, also known as a renewable natural gas, can be directly blended with or fully replace natural gas in existing pipelines and end-user equipment, with the added advantage of being carbon neutral. CO2 capture and storage (CCS) will also be of paramount importance in abating CO2 emissions from existing infrastructure in the power and industrial sectors. There are many industries that will be difficult or impossible to decarbonize in the short term, such as the cement sector, in which CO2 emissions are intrinsic to the production process. In such cases, CCS will be mandatory to achieve the goal of net zero emissions. Permanent CO2 removal technologies, such as bioenergy with carbon capture and storage (BECCS) and direct air capture and storage (DACS), will also be necessary in the medium term to compensate for emissions from the hard-to-abate sectors, and in the long term, even to remove atmospheric CO2 from past emissions. This book consists of six peer-reviewed scientific articles that cover a range of high-interest subjects related to the aforementioned hot topics.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.018 |
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".