Modelling inter-activity duration to capture weekly activity-travel dynamics: instilling inherent dynamics within daily travel demand models
Bibliographic record
Abstract
Explicitly modelling the multi-day dynamics can result in an accurate and unbiased understanding of activity-travel choices. The study introduces a copula approach to jointly model individuals’ inter-activity duration and travel mode choices using week-long travel diaries. This study uses the simulated likelihood technique to address the inherent left-censoring issue in inter-activity duration modelling using week-long travel diaries. The joint model is empirically estimated using week-long travel diaries collected in the Greater Toronto and Hamilton Area (GTHA), Canada. Seven mandatory and discretionary activity types are examined. The empirical model reveals a statistically significant dependency between inter-activity duration and travel mode choices. This dependency indicates that the frequent scheduling of specific activity types is positively correlated with higher utility from travel mode choices, particularly for retail shopping and service activities. Conversely, work/study and errand/grocery shopping activities show lower correlations, suggesting that higher mode choice utility has a lesser impact on the time between these activities.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".