Passenger Transport Management Methodology Based on the Econometric Analysis of Demand for Trans-Regional Transportation in Respect to the Innovation Economic Development Stage
Bibliographic record
Abstract
Transport complex is one of the fields of the RF forming infrastructure economy, which state influences national economy branches complexes development, interrelation of the economy branches, industry branches, and territorial complexes. On the one hand, transport as a market segment carries out goods exchange and renders services to population, and, on the other hand –as a market entity, it sells its services by transferring goods and passengers. Different kinds of transport render these services differently, thereby forming transport market. The development of transport is attributed to the growth of any country’s productive forces and its external relations. Complexity and low development level of formation and strategy realization problem of railway passenger transportation management, as well as need for further deepening the theory and practice of its prospects for development predetermined the topic choice and relevance in respect to the innovation stage of the Russian economy development. The methodology of demand for trans-regional railway passenger transportation in the RF and its main parameters depending on various economic factors based on author econometric model is developed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".