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Record W2980498607 · doi:10.36580/rgem.i3.41-57

Explorando Patrones y Controles en la Hidroquímica de Corrientes Proglaciales en el Alto Río Santa, Perú

2017· article· es· W2980498607 on OpenAlexaff
Alex Eddy, Bryan G. Mark, Michel Baraër, Jeffrey M. McKenzie, Alfonso Fernández, Susan Welch, Sarah K. Fortner

Bibliographic record

Venuenot available
Typearticle
Languagees
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcGill UniversityÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La dramática pérdida de glaciares en la cuenca alta del río Santa en Ancash, Perú, tiene un impacto significativo en los sistemas hidrológicos proglaciales, con implicaciones para los factores estresantes aguas abajo en las actividades de uso humano del agua. Este estudio integra el análisis hidroquímico y la exploración espacial en múltiples escalas con el objetivo de explorar patrones y controles de la calidad del agua inorgánica en la región. La química de las aguas superficiales proglaciales está determinada principalmente por la intemperie en las áreas de contacto agua-roca, y el agua de deshielo glacial hereda las propiedades químicas de la litología superficial a lo largo de un camino de flujo. Los métodos de análisis hidroquímico identifican características elementales que son exclusivas de la región de estudio. Los procesos hidroquímicos dominantes incluyen la meteorización del silicato, la oxidación de pirita acoplada con el desgaste del silicato y, en menor medida, la meteorización del carbonato. El constituyente de sulfato es inusualmente alto para partes de la región de estudio y se atribuye a aguas altamente acidificadas inmediatamente aguas abajo de fuentes puntuales glaciales. La geovisualización amplía los resultados del análisis hidroquímico al mostrar cambios temporales y sugerir conexiones entre áreas de litologías superficiales recién expuestas, altas tasas de erosión y meteorización, y concentraciones elevadas de sulfato.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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