Evaluación del sistema de tratamiento de aguas residuales del Instituto Tecnológico de Costa Rica.
Bibliographic record
Abstract
En el Instituto Tecnologico de Costa Rica (ITCR), sede Cartago, el lirio acuatico (Eichhornia crassipes) ha sido empleado en el tratamiento de sus aguas residuales. Dado que el sistema no habia sido evaluado, se presentan y analizan los resultados obtenidos durante setiembre de 1988 a mayo de 1989. El influente y el efluente del sistema fueron muestreados y analizados dos veces por semana, determinandose los parametros siguientes: demanda bioquimica de oxigeno (DBO), demanda quimica de oxigeno (DQO), oxigeno disuelto (OD), temperatura (T), pH, alcalinidad, turbiedad, conductividad, solidos totales (ST), solidos totales volatiles (STF), solidos suspendidos totales (SST), solidos suspendidos volatiles (SSV), solidos suspendidos fijos (SSF) y solidos sedimentables; los coliformes totales y fecales se determinaron cada cinco semanas. Las eficiencias de remocion promedio durante el estudio fueron 81% para DQO y 85% para la DBO, obteniendose mejores resultados durante la epoca seca (87% y 88% respectivamente). Los analisis se realizaron segun los metodos estandarizados para aguas residuales y los datos se analizaron por el metodo Gumbel. En conclusion, puede decirse que el lirio acuatico es capaz de bajar los contaminantes hasta niveles que cumplen con los limites establecidos en paises como Estados Unidos, Mexico y Canada.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".