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Record W2066968030 · doi:10.1029/2011eo210006

Identifying climate change threats to the arctic archaeological record

2011· article· en· W2066968030 on OpenAlexaff
M. S. Murray, Anne M. Jensen, Max T. Friesen

Bibliographic record

VenueEos · 2011
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArchaeological recordArcticClimate changeHoloceneArchaeologyPaleoclimatologyProxy (statistics)Environmental changeGeographyGeologic recordRange (aeronautics)Physical geographyOceanographyGeologyPaleontology

Abstract

fetched live from OpenAlex

Global Climate Change and the Polar Archaeological Record; Tromsø, Norway, 15–16 February 2011 ; A workshop was held at the Institute of Archaeology and Social Anthropology, University of Tromsø, in Norway, to catalyze growing concern among polar archaeologists about global climate change and attendant threats to the polar archaeological and paleoecological records. Arctic archaeological sites contain an irreplaceable record of the histories of the many societies that have lived in the region over past millennia. Associated paleoecological deposits provide powerful proxy evidence for paleoclimate and ecosystem structure and function and direct evidence of species diversity, distributions, and genetic variability. Archaeological records can span most of the Holocene (the past ∼12,000 years), depending upon location, and paleoecological records extend even further. Most are largely unstudied, and, although extremely vulnerable to destruction, they are poorly monitored and not well protected. Yet these records are key to understanding how the Arctic has functioned as a system, how humans were integrated into it, and how humans may have shaped it. Such records provide a wide range of data that are not obtainable from sources such as ice and ocean cores; these data are needed for understanding the past, assessing current and projecting future conditions, and adapting to ongoing change.

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 categoriesScience and technology studies, Insufficient 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 score0.387
Threshold uncertainty score0.999

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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.005

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 head0.335
GPT teacher head0.434
Teacher spread0.100 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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