Modeling Daily Activity Program Generation Considering Within-Day and Day-to-Day Dynamics in Activity-Travel Behavior
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Bibliographic record
Abstract
This paper presents Kuhn-Tucker demand system models for daily activity program generation. The models are for day-specific activity program generations of a week-long modeling span. The models accommodate within-day and day-to-day dynamics in time-use and activity-travel behavior explicitly. The activity types considered are the non-skeletal and flexible activities. These activities are divided into 15 generic categories. Under the daily time budget and non-negativity of participation rate constraints, the models predict the optimal set of activities (given the average duration of each activity type). The daily time budget considers the at-home basic needs and night sleep activities as a composite activity. The concept of composite activity ensures the behavioral dimension of time allocation and activity/travel behavior in a sense that the activities corresponding to the composite activity are regular skeletal activities but highly flexible in nature. We are sure to execute these activities but do not often allocate precisely a specific amount of time to them during advanced planning. Workers? total working hours (skeletal activity and not a part of the time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model. The incorporation of previous day?s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality condition used. The models use the concept of goal/direct utility of activity episodes. The empirical estimations of the models are done using 2002-2003 CHASE survey data collected in Toronto. The models perform well in terms of fitting the observed data.
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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 | 0.027 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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