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Record W2096033040 · doi:10.7202/014755ar

Late Quaternary Vegetation History of Northern North America Based on Pollen, Macrofossil, and Faunal Remains*

2007· article· en· W2096033040 on OpenAlexaffvenue
Arthur S. Dyke

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsMacrofossilBiomeHoloceneDeglaciationGeologyLast Glacial MaximumDisequilibriumQuaternaryClimatologyPhysical geographyEcosystemOceanographyPaleontologyGeographyEcology

Abstract

fetched live from OpenAlex

Biome maps spanning the interval from the last glacial maximum to modern times are presented. The biome distributions at 18 ka BP were probably as nearly in equilibrium with climate as are the modern distributions, but deglacial biomes were probably in disequilibrium. Ice sheet configuration was a strong control of climate until 7 ka BP. Regional climate trends can be inferred from changing biome distributions, but during periods of disequilibrium, biome distributions under-represent summer warming. Because of summer cooling by 2-4 °C during the Holocene, largely in the last 3-5 ka, middle and certain early Holocene biome distributions and species compositions are reasonable analogues of future equilibrium displacements due to equivalent warming, at least in areas that were long-since deglaciated. Past biome migration rates in response to rapid regional warming during deglaciation were mainly in the range of 100-200 m per year. If these rates pertain in the future, biomes may shift 10-20 km in most regions over the next century. A major impediment to using former Holocene conditions as a guide to future conditions is that warmer Holocene summers were accompanied by colder winters, whereas warmer future summers will be accompanied by warmer winters.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.969
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations145
Published2007
Admission routes2
Has abstractyes

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