Impact of Idling on Engine Temperatures in Winter Conditions
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">This study aimed to evaluate the impact of the duration of idling on engine warm-up and engine cool-down, and to assess the effectiveness of an energy recovery system. The results confirmed that there is no need to idle an engine for extended periods after a cold start to warm it up. It is more efficient to idle the engine for a short period, and then drive the vehicle or operate the machinery at moderate loads until the engine warms up to normal operating temperatures. The tests also confirmed that the engine retains enough heat for easy starting even after being shut down for a few hours and there is no need to idle an engine for fear of having cold start problems. The tests with an energy recovery system, which circulates engine coolant to the heater after the engine is shut down, showed that the system can maintain cab temperatures at comfortable levels even after the engine has been shut down for a few hours. This product would be ideal for day cab applications where idle periods rarely exceed one or two hours, or on heavy equipment that currently do not employ anti-idle technologies. The series of tests were performed were on a truck engine, yet the results can be applied to most diesel engines in trucks and heavy machinery.</div></div>
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".