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
In 2011, for the first time, Census in India reported travel distance and mode of travel for the workers. The distance reported is in the form of aggregate counts for each mode of travel in 7 distance bins (0-1 km, 2-5 km, 6-10 km, 11-20 km, 21-30 km, 31-50 km, and >50 km). In this data article, methods are described to model categorical count data as distance-decay functions using continuous probability distributions. The distributions have been developed for 8 categories of modes-walk, cycle, motorised two-wheelers, car, tempo/auto rickshaw/taxi, bus, train, and all modes combined, for the 33 mainland states of India and all states combined. Distance for walk is modelled using exponential distribution, and for all the other modes using lognormal or Weibull distribution. For estimating parameters of the distributions, chi-square minimization has been used in a spreadsheet program. The data presented includes parameters of the 272 (34 × 8) probability distributions as well as descriptive statistics of these distributions.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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