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
The primary objective of this paper is to “make the case” for adoption of microsimulation frameworks for development of integrated urban models. Similar to the case of activity-based travel models, microsimulation in integrated urban models enables such models to deal better with: heterogeneity and non-linearity in behavior; identification of the detailed spatial and socioeconomic distribution of impacts, benefits and costs; tracing complex interactions across agents and over time; providing support for modelling memory, learning and adaptation among agents; computational efficiency; and emergent behavior. The paper discusses strengths, weaknesses and challenges in microsimulating urban regions, including the extent to which microsimulation models are still subject to Lee’s famous “seven sins of large-scale modelling,” as well as the extent to which they may help alleviate or reduce these sins in operational models. The paper concludes with a very brief discussion of future prospects for such models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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