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Strontium and <sup>87</sup>Sr/<sup>86</sup>Sr isotopic ratio of ground brines in the northeastern Angara-Lena artesian basin

2021· article· en· W3176701544 on OpenAlexaboutno aff
Л. П. Алексеева, S. V. Alekseev

Bibliographic record

VenueEarth sciences and subsoil use · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsIsotopes of strontiumGeologyStrontiumGeochemistrySedimentary rockBrineMineralogyGroundwaterHaliteEvaporiteStable isotope ratioStructural basinChemistryGeomorphology

Abstract

fetched live from OpenAlex

The purpose of this study is to identify the major formation processes of the ionic and isotopic composition of chloride brines in the sedimentary basins of the Siberian platform. The object and subject of research are deep-seated strong, very strong and extremely saturated brines as well as their strontium content and the ratio of Sr stable isotopes. The groundwater ionic-salt composition was determined by traditional methods (titrimetric, gravimetric, flame photometry), the 87Sr/86Sr isotopic ratio was measured using mass-spectrometers (Irkutsk, Russia and Canada). The brines lying at the depth of 1500–3000 m were tapped and classified into saline and subsalt hydrogeological formations. Their feature is high salinity (385–530 g/L) and high content of strontium (2.3–7 g/L). The 87Sr/86Sr isotopic ratio ranges from 0.708 to 0.713062. By isotopic composition most of the brine samples are close to the waters of the Vendian-Cambrian paleoocean. However, some brine samples from the subsalt part of the sedimentary section of the basin are significantly enriched in the isotope 87Sr compared to the paleoocean waters and other samples. It could be due to the substantial input of 87Sr into the brines during the long-term interaction of groundwater with the host Lower Cambrian sandstones.

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 score0.015
Threshold uncertainty score0.030

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)0.0010.000

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 head0.027
GPT teacher head0.205
Teacher spread0.177 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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