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Record W2389437609

Chemical Characteristics and Seasonal Variation of Snow on Urumqi Glacier No.1 of the Eastern Tianshan,China

2011· article· en· W2389437609 on OpenAlexaff
Feiteng Wang

Bibliographic record

VenueEarth Science(Journal of China University of Geosciences) · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsScience North
Fundersnot available
KeywordsSnowGlacierSeasonalityEnvironmental scienceSpring (device)Air temperatureAtmospheric sciencesClimatologyPhysical geographyGeologyGeographyGeomorphologyEcology
DOInot available

Abstract

fetched live from OpenAlex

Alpine glacier and snow can record signals of surface earth.From September 2002 to October 2005,Surface snow samples were collected on Urumqi glacier No.1 and chemical characteristics and seasonal variations of major ions,dust,and metal were measured.Results show that the concentration of major ions is Ca2+SO2-4NO-3Cl-NH+4Mg2+Na+K+,Ca2+ is the dominant cation,SO2-4 is the dominant anion.All ions have good correlation except NO-3.δ18O shows minus correlation with air temperature change.Dust and major ionic concentrations in the snow show obvious seasonal change trend,with higher concentrations in spring but lower ones in summer,which indicates the chemical input of dust activities to snow.Temporal changes of heavy metal(Cd,Pb,Zn,Al,Fe) indicate that human activities also have effect on the snow chemistry.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.172
Teacher spread0.159 · 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 teacher head, 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
Published2011
Admission routes1
Has abstractyes

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