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
Non-fossil fuel energy options can help reduce or eliminate the emissions of greenhouse gases and are needed to combat climate change. Three distinct ways in which non-fossil fuel options can be used in society are examined here: the capture/production of non-fossil fuel energy sources, their conversion into appropriate energy carriers and increased efficiency throughout the life cycle. Non-fossil fuel energy sources are insufficient to avoid global warming in that they are not necessarily readily utilisable in their natural forms. Hydrogen energy systems are needed to facilitate the use of non-fossil fuels by converting them to two main classes of energy carriers: hydrogen (and hydrogen-derived fuels) and electricity. High efficiency is needed to allow the greatest benefits to be attained from energy options in terms of climate change and other factors. A case study is considered involving the production of hydrogen from non-fossil energy sources via thermochemical water decomposition. Thermochemical water decomposition provides a realistic future non-fossil fuel energy option, which can be driven by non-fossil energy sources (particularly nuclear or solar energy) and help combat global warming.
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 | 0.000 | 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 | 0.001 | 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 it