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Record W2912310376 · doi:10.24057/2071-9388-2018-50

Lateglacial And Early Holocene Environments And Human Occupation In Brandenburg, Eastern Germany

2019· article· en· W2912310376 on OpenAlexfundno aff
Franziska Kobe, Martin Bittner, Christian Leipe, Philipp Hoelzmann, Tengwen Long, Mayke Wagner, Romy Zibulski, Pavel E. Tarasov

Bibliographic record

VenueGEOGRAPHY ENVIRONMENT SUSTAINABILITY · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaFreie Universität Berlin
KeywordsHolocenePhysical geographyGeologyGeographyEarth scienceArchaeologyPaleontology

Abstract

fetched live from OpenAlex

The paper reports on the results of the pollen, plant macrofossil and geochemical analyses and the AMS 14C-based chronology of the «Rüdersdorf» outcrop situated east of Berlin in Brandenburg (Germany). The postglacial landscape changed from an open one to generally forested by ca. 14 cal. kyr BP. Woody plants (mainly birch and pine) contributed up to 85% to the pollen assemblages ca. 13.4–12.5 cal. kyr BP. The subsequent Younger Dryas ( YD) interval is characterized by a decrease in arboreal pollen (AP) to 75% but led neither to substantial deforestation nor spread of tundra vegetation. This supports the concept that the YD cooling was mainly limited to the winter months, while summers remained comparably warm and allowed much broader (than initially believed) spread of cold-tolerant boreal trees. Further support for this theory comes from the fact that the relatively low AP values persisted until ca. 10.6 cal. kyr BP, when the «hazel phase» of the regional vegetation succession began. The postglacial hunter-gatherer occupation is archaeologically confirmed in Brandenburg since ca. 13 cal. kyr BP, i.e. much later than in the western part of Germany and ca. 1000 years after the major amelioration in the Rüdersdorf environmental record.

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 score0.008
Threshold uncertainty score0.765

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 studies0.0000.001
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 head0.006
GPT teacher head0.247
Teacher spread0.241 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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Same venueGEOGRAPHY ENVIRONMENT SUSTAINABILITYSame topicPleistocene-Era Hominins and ArchaeologyFrench-language works237,207