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Record W191836162 · doi:10.1057/9781137062390_4

Greenland Norse Knowledge of the North Atlantic Environment

2012· book-chapter· en· W191836162 on OpenAlexaboutno aff
Thomas W. N. Haine

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2012
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsNorwegianGeographyViking AgeHuman settlementSettlement (finance)ArcticOceanographyClimate changeArchaeologyGeology

Abstract

fetched live from OpenAlex

T he arcing Norse expansion across the subpolar North Atlantic Ocean traces an inspiring tale of a stoic struggle against the elements. The sequence of accidental discovery, then deliberate exploration and settlement, repeated in turn as Faroe, Iceland, and Greenland were colonized between 825 and 985 AD. With each step further west, the difficulty of leading a contemporary Norwegian lifestyle increased. In part, the increasing hardship is linked to the increasing distance from European power, and the dwindling access to essential commodities. Contact with alien native communities is another factor, and it was decisive in obstructing long-term Norse settlements in North America. But at almost every stage, the much colder, more polar climate in Iceland, Greenland, and eastern Canada dominated the Atlantic Norse decision-making. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.138
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.003

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 head0.022
GPT teacher head0.215
Teacher spread0.193 · 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
GenreOther

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

Citations1
Published2012
Admission routes1
Has abstractyes

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