Carbon capture surfaces: Supporting Canada’s agricultural sector and climate ambitions
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
Carbon capture surfaces: Supporting Canada’s agricultural sector and climate ambitions Canada is positioning itself as a global leader in carbon dioxide removal (CDR) as it addresses climate change and creates economic opportunities for farmers. Beth McDaniel, JD from Reactive Surfaces explains how. As the world accelerates its efforts to combat climate change, removing existing carbon dioxide (CO2) from the atmosphere has become an essential tool in the fight to limit global warming. According to the International Energy Agency (IEA), as of early 2025, total operational carbon capture and storage capacity worldwide is just over 50 million tonnes per year. However, direct air capture (DAC) – technologies that capture and sequester CO2 directly from ambient air – represents only a small portion of that total, with current capacity standing at approximately 10,000 tonnes per year (IEA, 2025).
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 | 0.001 |
| 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