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
<div class="htmlview paragraph">This paper assesses the impact of the cold start phase of light duty vehicle use on energy use based on a review of large set of vehicle emissions test data from Canadian and U.S. Government databases. The data indicate that, at 24°C test ambient, a 20% increase in fuel use is measured in the “cold” Bag 1 driving compared with the “hot” Bag 3. Lower ambient conditions increase this penalty in a linear manner such that at the -6.7°C test condition, the penalty rises to 40-80%.</div> <div class="htmlview paragraph">The paper then integrates the laboratory tests data with vehicle demographic and usage data gathered from consumer driving studies. Included in this data are results from a small pilot survey in Vancouver, which directly measured instantaneous fuel consumption of vehicles in consumer use. These data sets were then used to estimate the total “extra” energy used during the cold start phase of driving. The analysis indicates that in Canadian urban centres, up to 25% of the total fuel use is due to cold engine effects.</div>
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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