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Record W3150939120 · doi:10.1080/17445647.2021.1898483

Alluvial Terraces and Contaminant Sources of the Santa Catarina River in the Monterrey Metropolitan Area, Mexico

2021· article· en· W3150939120 on OpenAlexaff
G. E. Martínez-Quiroga, Héctor de León-Gómez, Fabiola D. Yépez-Rincón, Sebastian Lopez-Saavedra, A. Cruz-López

Bibliographic record

VenueJournal of Maps · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of Alberta
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsHydrology (agriculture)AlluviumGeologyGroundwaterTributaryMetropolitan areaGeomorphologyGeographyCartographyArchaeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

The development of the Monterrey Metropolitan Area (MMA) and human carelessness have severely altered the Santa Catarina River (SCR). The objective of this research was to integrate fieldwork, a digital elevation model, exploratory surveys and satellite images analysis to develop a GIS-based map scale 1:40,000 and 1:5,000 of the Quaternary alluvial terraces and Cretaceous geologic formations present in the SCR. In addition, this study presents river geologic cross-sections, hydraulic conductivity estimates per terrace, a piezometric chart (dry season), and a database of contaminant sources along the river. The main results were the following: three terraces levels were identified, the distribution and hydrogeological properties of the terraces were documented, groundwater flow direction was southwest (SW) to northeast (NE), and 154 contaminant sources were georeferenced. This investigation lays down the basis for future environmental assessments and studies related to the quality and water supply for the MMA.

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 score0.229
Threshold uncertainty score0.455

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.197
Teacher spread0.186 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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