Сравнительный анализ Европейского и североамериканского вариантов для третьего этапа реформирования российского железнодорожного транспорта
Bibliographic record
Abstract
Russian rail has been restructured since 2001. Now it is passing through the third and last stage prolonged for 2015. For further determination of the development strategy for the Russian railway transport, it is needed to compare the three groups of factors: conditions of its operation and performance parameters; economic situation in the rail sector; objectives of the rail restructuring in Russia and in the countries of the two basic models of rail operation. The two basic models are called North American (vertical integration of competing companies) and European (vertical separation of infrastructure and freight operations). The article shows significant similarity of the said three groups of factors in the Russian rail sector and in the rail sectors of North American model’s countries (the USA, Canada, Mexico) as well as principal differences of those groups of factors in Russia and in European model’s countries (the UK, the EU).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".