SISTEMA AUTOMATIZADO PARA BANCO DE PRUEBA DE LOCOMOTORAS (BPLW)
Bibliographic record
Abstract
Se explica el funcionamiento del Sistema BPLW disenado para los Bancos de Prueba de Locomotoras canadienses MLW, que automatiza el proceso de pruebas y mediciones en los mantenimientos y/o reparaciones. Se describe la continuidad del proceso de automatizacion del Banco de Pruebas de Locomotoras de los talleres de ferrocarriles Jose Ramirez Casamayor. Se ha realizado el diseno sobre Windows y Visual C++, por lo que presenta facilidades visuales y de dialogo que simplifican las tareas del operador. Resumen en ingles: The present article explaind the System BPLW designed for the Banks os Test of Canadian Locomotives MLW that automates the process of tests and measurement of their parameters as part of the maintenance and/or repairs, offering the option of measuring in an independent way the aggregates of the Diesel Generator of other locomotives. It is possible to carry cut the tests of Adjustment, Settling and Consumption of Fuel, in an assisted way, since it goes indicating to the operator the actions to take. In cash operation. great utility for the operatiors of Banks of Tets, since it decrease in a considerable wayt time of execution of the tests, the human errors and time in the detection of technical problems of all type; with what an important increment is obtained in the quality of the tests. (A).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.014 |
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".