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Record W2766418456 · doi:10.1177/0959683617735583

Variations in precipitation in North America during the past 2000 years

2017· article· en· W2766418456 on OpenAlexaff
Marco Ladd, A. E. Viau, RG Way, Konrad Gajewski, MC Sawada

Bibliographic record

VenueThe Holocene · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBorealPeriod (music)PrecipitationClimatologyPhysical geographyTaigaPollenPaleoclimatologyGeologyGeographyOceanographyClimate changeArchaeologyEcologyForestry

Abstract

fetched live from OpenAlex

We present a 2000-year pollen-based reconstruction of total annual precipitation (ANNP) for North America. Application of Local Indices of Spatial Association (LISA) permitted us to distinguish regional large-scale hydroclimate patterns from local site-specific conditions across North America during this time period. Century-scale filtered pollen-based reconstructions are more spatially coherent than unfiltered reconstructions, allowing for better identification of past hydroclimate patterns across North America. Similar spatial patterns dominated during both the ‘Medieval Warm Period’ (MWP; 950–1250 CE) and Roman Warm Period (RWP; 50 BCE–150 CE), although the MWP was generally drier than the RWP. In contrast, hydroclimate changes during Dark Ages Cold Period (DAC; 350–650 CE) and the ‘Little Ice Age’ (LIA; 1550–1850 CE) show opposing patterns across the western and eastern boreal region of North America. During warm periods, eastern and western boreal regions had similar moisture condition, whereas during cold periods, the eastern boreal region was relatively wet and the west was dry.

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)0.000
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 score0.022
Threshold uncertainty score0.696

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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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

Citations25
Published2017
Admission routes1
Has abstractyes

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