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Record W2375049792

Temporal and spatial distribution and long-term variation trend of precipitation in Xi'an

2010· article· en· W2375049792 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGanhanqu ziyuan yu huanjing · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Changes in China
Canadian institutionsScience North
Fundersnot available
KeywordsPrecipitationSpatial distributionEnvironmental scienceClimatologySpatial variabilityWet seasonSpring (device)SeasonalityPeriod (music)Trend analysisAtmospheric sciencesGeographyGeologyMeteorologyEcologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

On the basis of precipitation data collected from seven gauging stations around Xi'an city during the period of 1961-2005,the temporal and spatial distribution of precipitation in Xi'an region was analyzed.The Mann-Kendall test was applied to analyze annual and seasonal precipitation time series.The temporal distribution included the variations of year,season and month for the whole region.For spatial distribution,the variation of the precipitation of year and season for the seven areas were determined.The results showed that the temporal and spatial distributions of precipitation was uneven and the mean annual precipitation had a decreasing trend from 1961-2005,which mainly resulted from the variation of precipitation in the spring and autumn,especially in spring,during which the slope was-1.98mm/a.While in summer and winter,the precipitation exhibited an increasing trend.The rainy season was concentrated in summer and autumn every year,and the total rainfall during the period from May to October occupied 79% of the annual precipitation.

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.

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)0.000
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 score0.111
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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