MétaCan
Menu
Back to cohort
Record W7011488551

Mejoramiento del servicio de agua a nivel parcelario con un sistema de riego en el centro poblado Marayhuaca, distrito de Incahuasi, provincia Ferreñafe, departamento Lambayeque

2022· dissertation· es· W7011488551 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2022
Typedissertation
Languagees
FieldEnvironmental Science
TopicWater Resource Management and Quality
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureSocial impactRural developmentWater supply
DOInot available

Abstract

fetched live from OpenAlex

El bajo rendimiento de los cultivos en el distrito de Incahuasi por la limitada disponibilidad e ineficiencia en el uso del recurso hídrico afecta directamente a los productores y su calidad de vida, es por eso que, en el presente proyecto se elabora la propuesta para el “Mejoramiento del servicio de agua a nivel parcelario con un sistema de riego tecnificado en el centro poblado Marayhuaca, distrito de Incahuasi, provincia Ferreñafe, departamento Lambayeque”, la población objetivo son 18 productores agrícolas usuarios del canal Marayhuaca-Rikchi de la comunidad campesina San Isidro Labrador de Marayhuaca, los mismos que cumplen los requisitos establecidos por la Ley 28585 para el acceso al financiamiento y que en conjunto poseen 18.42 ha; el tipo de riego a instalar es por goteo para el cultivo de arveja, que presenta una demanda hídrica con proyecto de 102 231 m3 al año y la oferta hídrica de 161 730 m3 anuales, entre los componentes del proyecto se encuentran las obras parcelarias, obras comunes, capacitación y la asistencia técnica; el costo privado del proyecto es de S/ 651 219.89 y el costo social es de S/ 551 348.06. Finalmente, en la evaluación social se obtuvo un valor actual de los costos de S/ 748 633 y un indicador de costo efectividad de S/ 41 590.74 por beneficiario, valor que es inferior al umbral del sector, por lo tanto, el proyecto es factible.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.723

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.008
GPT teacher head0.264
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuerenatiSame topicWater Resource Management and QualityFrench-language works237,207