Bibliographic record
Abstract
While the chemical energy in fossil fuels has enabled the rapid rise of modern civilization, their utilization and accompanying anthropogenic CO2 emissions is occurring at a rate that is outpacing nature's carbon cycle. Its effect is now considered to be irreversible and this could lead to the demise of human society. This is a complex issue without a single solution, yet from the burgeoning global research activity and development in the field of CO2 capture and utilization, there is light at the end of the tunnel. In this article a couple of recent advances are illuminated. Attention is focused on the discovery of gas-phase, light-assisted heterogeneous catalytic materials and processes for CO2 photoreduction that operate at sufficiently high rates and conversion efficiencies, and under mild conditions, to open a new pathway for an energy transition from today's "fossil fuel economy" to a new and sustainable "CO2 economy". Whichever of the competing CO2 capture and utilization approaches proves to be the best way forward for the development of a future CO2-based solar fuels economy, hopefully this can occur in a period short enough to circumvent the predicted adverse consequences of greenhouse gas climate change.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".