Diagnóstico de la condición de desgaste basado en el análisis de aceite usado. Caso de estudio: Vehículo de servicio de taxi
Bibliographic record
Abstract
Las condiciones operativas del motor de un vehículo, dependen del combustible, lubricante y los componentes, para ello se plantea el diagnóstico directamente por un monitoreo continuo del lubricante. Este proyecto evalúa la condición de desgaste del motor por encendido provocado en un vehículo de uso público tipo taxi, aplicando la técnica de análisis de lubricante usado.El proceso de investigación es experimental, se levanta una línea base del lubricante y vehículo, para la toma de muestras cada 4000 kilómetros de recorrido, en cada muestra se analiza las propiedades físicas y químicas del lubricante, se establece el comportamiento de la viscosidad, partículas contaminantes y partículas metálicas del MEP del vehículo. El comportamiento del índice PQ y partículas metálicas, muestra una tendencia constante para el desgaste, el índice PQ combinado con un bajo número ppm de hierro indica una tendencia de desgaste normal, también, se descarta la contaminación por el ambiente que rodea el funcionamiento del MEP, indicativo de una incidencia leve para desgaste abrasivo en las piezas móviles del motor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".