Bibliographic record
Abstract
Abstract Use of fossil fuel ever since the dawn of the industrial age has led to increased level of CO2 in the environment. Our world today is fueled mainly by fossil energy and it is unlikely that this dependence will significantly change in the near future. This coupled with the fact that majority of the developing world is at the beginning of the economic growth which is implicitly energy-intensive, the concentration of CO2 in atmosphere will only increase in the business-as-usual case. Reduction in per capita CO2 emission both on account of minimizing explicit wastes and improving efficiencies will play a significant role in slowing down the build up of CO2. But to bring its concentration down and back to the preindustrial or comfortable levels, emphasis may have to shift to CO2 sequestration. This paper discusses the role and potential of geological and biological sequestration approaches. Furthermore, for a longer time horizon it highlights the importance and practicality of a modified approach to bio-sequestration, where CO2 is captured and stored on surface by Carbonization of biomass through its conversion to charcoal. It highlights the fact that biosequestration can be very effective and practical but requires achievement of longer bio-storage duration which is achievable through conversion to charcoal. Also, combinations of various approaches including geological sequestration and efficiency improvement are essential to reverse the trend of increasing concentration of CO2 in the atmosphere in a short run.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".