MétaCan
Menu
Back to cohort
Record W4210335604 · doi:10.52109/cyp2022321

Determinación de la calidad del agua del Río Caldera, Boquete, Chiriquí

2022· article· es· W4210335604 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCiencia y Práctica · 2022
Typearticle
Languagees
FieldEnvironmental Science
TopicWater Resource Management and Quality
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHumanitiesForestryMineralogyPhysicsChemistryArtGeography

Abstract

fetched live from OpenAlex

El presente estudio evalúo la calidad del agua del río Caldera, uno de los ríos más importantes de la provincia de Chiriquí, el cual abastece al distrito de Boquete, tanto para consumo humano, como para fines agrícolas y ganaderos. Fueron medidos tres sitios del río Caldera (parte alta, media y baja), obteniéndose los promedios de parámetros de temperatura del agua (20,55 °C), conductividad eléctrica (69,37 µS cm-1) y pH (7,5). Comparando los datos obtenidos con los valores del Reglamento Técnico DGNTI-COPANIT 23- 395 –99 de agua potable: los niveles de pH mantienen un rango permisible (6,5 – 8,5), los TDS indican un agua de poca mineralización (<100 mgL-1), la conductividad menor al límite estipulado (850 µScm-1) y la temperatura inferior a 28 °C es óptima. Los resultados indican una buena calidad de agua según los parámetros estudiados; sin embargo, de los cinco metales estudiados (Al, Cd, Cr, Cu y Pb), la mayoría presentó concentraciones menores a los límites establecidos; a excepción del cadmio, el cual sobrepasa el límite de 0,003 mgL-1 de acuerdo con la legislación establecida.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.014
GPT teacher head0.262
Teacher spread0.249 · 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