Empirical Investigation of Household Vehicle Type Choice Decisions
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
Automobile ownership models are an integral part of comprehensive transportation modeling systems. Recent work and ongoing advances in the area of activity-based travel demand modeling have recognized the need for increased experimentation with automobile choice models. On the other hand, while automobiles are very important in people's everyday lives, they also have a serious impact on the environment. This impact occurs at the micro level (pollution) as well as the macro level (emission of greenhouse gases and global warming). Such impacts have led to increased interest in reducing motor vehicle emissions. A household automobile type choice model was developed at a disaggregate level. The model can provide a direct forecast of consumer demand for personal-use vehicles given the available choices. A well-developed form of discrete choice modeling techniques, the nested logit model, was used to investigate the process of household automobile type choice decisions given that a transaction has occurred.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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