Analyse orientée-objet et totalement désagrégée des données d'enquêtes ménages origine-destination
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
Large urban household surveys produce a huge quantity of data, generally processed with database management systems (DBMS). In most cases, data are compiled, aggregated, and then integrated in traditional transportation models. Based on another perspective, the totally disagregate approach (TDA) uses a unified survey data file in which every piece of information is preserved. The data file is used for individual analysis of households, people, and trips. The addition of an object-oriented modeling to the totally disaggregate approach permits the instantiation of survey data into objects. These objects are manipulated along with their properties and methods. New objects are derived from survey declaration and then reused in the process: status, trip generators. The enriched object-model is used for visualization, analysis, and presentation. This widens the possibilities of usage of household survey data.Key words: urban transportation, household surveys, modeling, oriented-object approach.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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