Methodology for the economic evaluation of CO2 derived materials
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
Abstract Scoring the technologies in competition for the NRG Canada’s Oil Sands Innovation Alliance Carbon XPRIZE required an economic evaluation to estimate the value created through the conversion of CO2 emissions into products. Across all of the Teams participating in the competition, 58 different materials were consumed and produced. Standardized prices and market sizes needed to be established for each of these materials to ensure a consistent evaluation across all Teams. The Standards Data Set (SDS) was created as a standardized database of economic data used in the competition. The rationale for the SDS project and the methodology for researching each material is described. Ultimately, credible material definitions using the SDS methodology were created for all materials, and some research and methodological customization were required for materials that did not have credible, publicly available market data. The methodologies for establishing credible values and market sizes for concrete, concrete admixtures and syngas are highlighted as examples of materials whose value and markets are not easily defined.
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 | 0.000 |
| 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