Week-long activity-based modelling: a review of the existing models and datasets and a comprehensive conceptual framework
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
Activity-based travel demand models emerged mainly to fix the conceptual, statistical, and operational deficiencies of conventional trip-based models. This is done by microstimulating the activity scheduling behaviour of individuals/households instead of modelling the number of trips between the zones of an urban area. In the “Next Generation” of activity-based models (ABMs), researchers are making an effort to improve their capacity to replicate the travel-activity patterns of urban populations more realistically. Expanding the modelling time frame from a single day to an entire week is one of the essential aspects of the “Next Generation” of ABMs. Although there is still a long way to go before a comprehensive and operational week-long ABM can be developed, the literature on its different aspects, the theoretical and conceptual frameworks, and the efforts to collect multi-day travel-activity diaries are now at a stage that is worth a comprehensive and systematic review. Therefore, the current study is devoted to exploring the existing literature on multi-day activity-based modelling, categorising its elements in a systematic manner, searching for the research gaps in the existing models and proposing a comprehensive framework to fill those gaps.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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