Bibliographic record
Abstract
Este artículo presenta los resultados de una simulación de flujo de agua subterránea en rocas fracturadas. Se emplea un enfoque estocástico (modelo estocástico equivalente en medio poroso fracturado) para construir el modelo conceptual y para usar este último en la roca de baja permeabilidad encontrada en el sitio elegido como caso de estudio (Olkiluoto, Finlandia). La roca que se investiga se encuentra localizada alrededor de un grupo de pozos de sondeo y cubre un área de algunas hectáreas. Las mediciones de campo de pruebas de interferencia hidráulica se utilizan para calibrar el modelo de flujo de agua subterránea. Múltiples combinaciones de facies estocásticos se consideran para evaluar el impacto de la distribución y del número de facies en las cargas hidráulicas y en los caudales. Este estudio cuantifica la variabilidad de los resultados numéricos, lo cual es importante para el análisis de la incertidumbre en los sistemas hidrogeológicos. Por otra parte, este estudio muestra que el modelo conceptual de facies estocásticos es una alternativa adecuada a los modelos conceptuales de redes de fracturas discretas.
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.
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 | 0.000 | 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) | 0.001 | 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".