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Record W1528460825 · doi:10.7202/033138ar

Postglacial Development of Kazakhstan Pine Forests

2007· article· en· W1528460825 on OpenAlexfundvenueno aff
Constantin V. Kremenetski, Pavel E. Tarasov, Aleksandr E. Cherkinsky

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersUniversité de Montréal
KeywordsFoothillsScots pineVegetation (pathology)SteppeForestryGeographyPeatAlderTaigaPhysical geographyEcologyArchaeologyBotanyPinus <genus>Biology

Abstract

fetched live from OpenAlex

Fossil pollen records from two peatlands and two lakes in Kazakhstan provide radiocarbon-dated evidence of vegetation change since 13 000 BP. During the Lateglacial open spruce (Picea obovata) forests started spreading along river valleys and over the Kazakhstan Foothills. By 9500 BP, the southern limit of spruce approached its present-day position. Between 9500 and 8000 BP steppe and open birch forests formed the vegetation in the south of the West Siberian Lowland. Dry steppe and semi-desert were the main types of vegetation in north Kazakhstan. From 7000 to 5500 BP Scots pine (Pinus sylvestris L.) expanded in Kazakhstan and reached its present day southern limit. Since 5500 BP pine has formed monospecific forests in the lrtysh-Semipalatinsk area and in the northern part of the Kazakhstan Foothills. By 5000 BP lime (Tilia cordata) penetrated into the northern part of the Kazakhstan Foothills. The ranges of oak (Quercus robur), elm (Ulmus glabra) and black alder (AInus glutinosa) also expanded. The period 4500-3600 BP was characterised by a drier and more continental climate. During that time, the forested area decreased. The ranges of broadleaved trees and alder were reduced. A phase of less continental climate occurred 3300-2800/ 2700 BP. By 1500 BP the present southern limit of Scots pine was established.

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 score0.830
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.273
Teacher spread0.256 · 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

Citations58
Published2007
Admission routes2
Has abstractyes

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