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Record W3013517662 · doi:10.1038/s41597-020-0445-3

A global database of Holocene paleotemperature records

2020· article· en· W3013517662 on OpenAlexaff
Darrell S. Kaufman, Nicholas P. McKay, Cody Routson, Michael P. Erb, Basil A.S. Davis, Oliver Heiri, Samuel L. Jaccard, Jessica E. Tierney, Christoph Dätwyler, Yarrow Axford, Thomas Brussel, Olivier Cartapanis, Brian Chase, Andria Dawson, Anne de Vernal, Stefan Engels, Lukas Jonkers, Jeremiah Marsicek, Paola Moffa‐Sánchez, Carrie Morrill, Anaïs Orsi, Kira Rehfeld, Krystyna M. Saunders, Philipp S. Sommer, Elizabeth K. Thomas, Marcela Sandra Tonello, Mónika Tóth, Richard S. Vachula, Andrei Andreev, Sébastien Bertrand, Boris K. Biskaborn, Manuel Bringué, Stephen J. Brooks, Magaly Caniupán, Manuel Chevalier, Les C. Cwynar, Julien Emile‐Geay, John M. Fegyveresi, Angelica Feurdean, Walter Finsinger, Marie-Claude Fortin, Louise Foster, Mathew Fox, Konrad Gajewski, Martín Grosjean, Sonja Hausmann, Markus Heinrichs, Naomi Holmes, Boris Ilyashuk, Elena A. Ilyashuk, Steve Juggins, Deborah Khider, Karin A. Koinig, Peter G. Langdon, Isabelle Larocque‐Tobler, Jianyong Li, André F. Lotter, Tomi P. Luoto, Anson W. Mackay, Enikő Magyari, Steven B. Malevich, Bryan G. Mark, Julieta Massaferro, Vincent Montade, Larisa Nazarova, Елена Новенко, Petr Pařil, Emma J. Pearson, Matthew Peros, Reinhard Pienitz, Mateusz Płóciennik, David F. Porinchu, Aaron P. Potito, Andrew Rees, Scott Reinemann, Stephen J. Roberts, Nicolas Rolland, J. Sakari Salonen, Angela Self, Heikki Seppä, Shyhrete Shala, Jeannine-Marie St-Jacques, Barbara Stenni, Liudmila Syrykh, Pol Tarrats, Karen Taylor, Valerie van den Bos, Gaute Velle, Eugene R. Wahl, Ian R. Walker, Janet M. Wilmshurst, Enlou Zhang, Snezhana Zhilich

Bibliographic record

VenueScientific Data · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusBishop's UniversityOkanagan CollegeGeological Survey of CanadaUniversity of OttawaUniversity of New BrunswickCenter for Northern StudiesConcordia UniversityUniversité du Québec à MontréalUniversity of British ColumbiaFisheries and Oceans CanadaMount Royal UniversityUniversité LavalNatural Resources Canada
FundersNational Oceanic and Atmospheric AdministrationSight Research UKClimate Program OfficeHeising-Simons FoundationPast Global ChangesNatural Environment Research CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsHolocenePaleoclimatologyProxy (statistics)PeatDatabaseGeologyContext (archaeology)Physical geographyClimate changeNorthern HemisphereClimatologyOceanographyGeographyArchaeologyPaleontology

Abstract

fetched live from OpenAlex

A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.012
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0120.024
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.005

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 head0.070
GPT teacher head0.291
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 designNot applicable
Domainnot available
GenreDataset

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

Citations300
Published2020
Admission routes1
Has abstractyes

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