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Record W3026523388 · doi:10.13227/j.hjkx.201812010

[Comparison of the Geochemical Characteristics of Karst Springs of a Vertically Zoned Climate Region under Human Activity: A Case of Shuifang Spring and Bitan Spring in the Jinfo Mountain Area, Chongqing].

2019· article· en· W3026523388 on OpenAlexaff
Guo-Wen Xie, Pingheng Yang, Ting Sheng, Shujin Deng, Aihua Hong

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsSpring (device)KarstGeologyHydrology (agriculture)PrecipitationLithologyGroundwaterCarbonateWater qualityCaveEnvironmental scienceGeochemistryEcologyChemistryGeotechnical engineering

Abstract

fetched live from OpenAlex

in Shuifang Spring, which peaked in winter and summer, while hydrochemical parameters of Bitan Spring changed smoothly throughout the year. The water quality of Bitan Spring is better than Shuifang Spring (Shuifang Spring water is classified as Class Ⅳ). PCA shows that the water-rock interaction was the first controlling factor. Hotel sewage discharge and ions from precipitation had important effects on Shuifang Spring and Bitan Spring, respectively. In addition, the effects of soil erosion and leaching caused by precipitation also impact on the water quality of two springs to some extent. The geochemical susceptibility of Shuifang Spring was greater than that of Bitan Spring; therefore, corresponding measures should be formulated according to the characteristics of these differently elevated karst systems when exploiting groundwater resources. This is especially the case for the treatment of hotel sewage.

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 score0.158
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.233
Teacher spread0.206 · 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
Published2019
Admission routes1
Has abstractyes

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