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Record W2174551625 · doi:10.5539/esr.v5n1p19

Climate-Driven Landformof the Ejina Basin (NW China) in Central Asia and Its Paleoenvironmental Implications

2015· article· en· W2174551625 on OpenAlexvenueno aff
Bingqi Zhu

Bibliographic record

VenueEarth Science Research · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsStructural basinWesterliesGeologyHoloceneLandformPhysical geographyAridAlluvial fanPleistoceneClimate changeGlacial periodAlluvial plainClimatologyGeomorphologyPaleontologyGeographyOceanography

Abstract

fetched live from OpenAlex

<p>Though neotectonic activity is believed to be the major factor in the evolution of the topography of the Ejina Basin in Central Asia, detailed documentation and analysis of climatic landscape features and their environmental implications are lacking. The present study is a site-specific documentation of landforms developed in the wide part of the Ejina Basin, with the aim to identify the climatic landforms based on the method of climatic geomorphology and to evaluate its landscape evolution and response to palaeoclimate changes. The morphodynamics of older landscapes are recognized by making comparison with the present climate and its corresponding landscapes. Clear evidences testifying the basin-scale shifting and transformation of different morphoclimatic zones in the basin are observed, which prove that the main geomorphic unit is changed from an alluvial-lacustrine plain to a desert plain. The coexistence of diverse landscapes and the consequent geomorphodiversity in the basin should be a compound result of surficial processes other than glaciations. The climate and hydrological conditions of the basin during the last glaciation and during the Early Holocene were much better than at present, possibly having an average annual precipitation ranged between 60~350 mm on <del cite="mailto:unknown" datetime="2015-11-27T09:00"> </del>the basin during ca. 39-23 ka BP but great fluctuations during Holocene. The periods of lower aridity during the late Pleistocene in the bain could be induced by an increase of the westerlies and a weakening of the Asian winter monsoon on the arid areas of the central Asia.</p>

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)0.005
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 score0.023
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.065
GPT teacher head0.327
Teacher spread0.262 · 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
Published2015
Admission routes1
Has abstractyes

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