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Record W2095044450 · doi:10.1016/j.yqres.2014.01.001

Human-ecosystem interactions in relation to Holocene environmental change in Port Joli Harbour, southwestern Nova Scotia, Canada

2014· article· en· W2095044450 on OpenAlexafffundabout
Karen Neil, Konrad Gajewski, Matthew Betts

Bibliographic record

VenueQuaternary Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsMusée de la CivilisationUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaNova Scotia Department of Energy
KeywordsHoloceneRadiocarbon datingGeologyPeatContext (archaeology)Physical geographyVegetation (pathology)WetlandEcologyOceanographyArchaeologyGeographyPaleontology

Abstract

fetched live from OpenAlex

Abstract A high-resolution pollen record from Path Lake in Port Joli Harbour, Nova Scotia, Canada, provides a paleo-ecological perspective on Holocene climate and vegetation variability within the context of local archaeological research. Pollen assemblages in the early Holocene reflect a post-glacial forest dominated by Pinus , Tsuga , Betula and Quercus . During this time, a lower frequency of radiocarbon dated cultural material suggests lower human settlement intensity. Shallow water aquatic ( Isoetes ) and wetland ( Alnus , Sphagnum ) taxa increased after 3400 cal yr BP in response to a transition towards wetter climatic conditions. Culturally significant periods, where settlement intensity increased in the Maritimes and Maine, coincide with maximum values of reconstructed total annual precipitation, suggesting that environmental conditions may have influenced prehistoric human activity. European settlement, after 350 cal yr BP, was marked by a rise in Ambrosia . The impact of anthropogenic fire disturbances on the landscape was evidenced by peak charcoal accumulations after European settlement.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.084
GPT teacher head0.332
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

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

Citations18
Published2014
Admission routes3
Has abstractyes

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