Historical Validation of Integrated Transport–Land Use Model System
Bibliographic record
Abstract
The Integrated Land Use, Transportation, Environment (ILUTE) model system is an agent-based microsimulation model for the greater Toronto–Hamilton, Ontario, Canada, area. The model system uses disaggregate models of spatial socioeconomic processes to evolve the state of the greater Toronto–Hamilton area from a known base case to a predicted end state in 1-year time steps. ILUTE has reached a state of operational implementation in which historical validation runs are being undertaken. The model runs start with 100% of the population of people, families, households, and dwelling units in the greater Toronto area that was synthesized for the year 1986. Twenty-year historical simulations (1986 to 2006) have been run, with model outputs being compared with Canadian census data and Transportation Tomorrow Survey data for 1991, 1996, 2001, and 2006. This paper presents recent findings from these historical validation tests and emphasizes the system's modeling of the demographic evolution of the population and the region's housing market.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".