Modelo estadístico para predecir la calidad del agua de consumo humano en el ámbito rural del "Callejón de Huaylas"
Why this work is in the frame
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Bibliographic record
Abstract
espanolObjetivo: Desarrollar un modelo estadistico para predecir la calidad del agua de consumo humano en el ambito rural del Peru, con el fin de disminuir las tasas de morbilidad y mortalidad producidas por enfermedades de transmision hidrica. Material y Metodos: Se trata de un estudio aplicado de nivel predictivo, prospectivo, de corte longitudinal, cuasi experimental. El area de estudio fue el Centro Poblado de Paria � Willcawain � Ancash y la muestra seleccionada fueron 35 hogares. La obtencion de las variables cuantitativas (parametros fisicos, quimicos y microbiologicos) se realizo siguiendo las Normas Internacionales (APHA � AWWA � WPCF, 1992) , en el Laboratorio de Calidad Ambiental � UNASAM; para cuantificar el indice de calidad del agua (ICA) se aplicaron diferentes metodos desarrollados en USA, Inglaterra, India y Canada. Para calcular los modelos predictivos se utilizo el programa Econometric Views 7.0 que utiliza los errores de Newey � West (HAC) y selecciona las variables de regresion significativas segun el tamano de la muestra y el grado de libertad, mediante el criterio de parsimonia, que genera la correccion automatica. Los modelos que tienen una mejor bondad de ajuste son: i) Periodo estiaje: ICA1 = 80.99-0.048(Morbi)-0.269(TD)0.066(Condu)-0.060(EC); ii) Periodo lluvia: ICA4 = 84.540.042(Morbi)-0.478(TD)-0.0817(Condu)-0.0135(BH). Como conclusion mas relevante se obtuvo que en los periodos de estiaje y lluvia el agua de consumoes aceptable, siendo de una mayor calidad. EnglishObjective: To develop a statistical model to predict the quality of drinking water in rural areas of Peru , in order to decrease the morbidity and mortality caused by waterborne diseases . Material and Methods: The study is applied predictive level, prospective, longitudinal, quasi-experimental. The study area was in the Town Center of Paria -Willcawain -Ancash, the selected sample were 35 homes, obtaining quantitative variables (physical parameters, chemical and microbiological) was performed according to International Standards (APHA � AWWA � WPCF, 1992) , in the Environmental Quality Laboratory � UNASAM; to quantify the rate of water quality (RWQ) was applied different methods developed in USA, England, India and Canada. To calculate predictive models were used the Econometric Views 7.0 program, which using Newey � West errors (HAC) that selects significant regression variables according to the sample size and the degree of freedom, with the parsimony criterion, which generates the automatic correction. The models have better goodness of fit are: i) Drought Period: ICA1 = 80.990.048(Morbi)-0269 (TD)-0.066(Condu)-0.060 (EC); ii) Rain Period: ICA4 = 84.54-0.042(Morbi)-0.478(TD)-0.0817(Condu)-0.0135 (BH). The conclusion most relevant was that in periods of drought and rain water quality is among polluted.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it