Environmental System Effects when Including Scrap Preheating and Surface Cleaning in Steel Making Routes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Agriculture has the potential to supply large amounts of biomass for renewable energy production from residues from traditional crop production and from dedicated energy crops.This renewable energy production has significant potential to contribute to the reduction of GHG emissions in the energy sector by using ethanol and biodiesel to displace petroleum based liquid fuels and direct burning of biomass to displace coal for generating electricity.To quantify this biomass potential, we used the Canadian Economic and Emissions Model for Agriculture to estimate renewable energy production from biomass and the impact on agricultural production.We used two scenarios: the first scenario that looks at a combination of market incentives and mandates, and a second scenario that looks at only market incentives.The results show that: in the markets and mandates scenario, biomass production is higher, both ethanol and electricity are required to take place and land use change occurs.Agriculture has significant potential to generate biomass for energy under different scenarios, the incentive mix can have a large impact on the type of bioenergy produced, there is significant potential for GHG emission reductions and there is potential for unintended GHG effects, such as the increased clearing of land for crop 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.
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 | 0.001 | 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 | 0.001 |
| 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 it