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Record W4396870867 · doi:10.1080/02723646.2024.2327225

Duke William’s 1066 campaign, the historical climatology

2024· article· en· W4396870867 on OpenAlex
Christopher Macdonald Hewitt

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Geography · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsWestern University
Fundersnot available
KeywordsClimatologyHistoryMeteorologyGeographyAncient historyGeology

Abstract

fetched live from OpenAlex

A number of studies have examined historical climatological trends back to the Middle Ages. However, few have investigated these trends near important historical sites such as medieval battlefields. Most studies on medieval battles and battlefields focus almost exclusively on interpreting the written records from a literary standpoint and on knowledge of the site on which the battle took place, with rarely much consideration for other perspectives. While the written records are important, only focusing on them limits understanding and ignores the environment itself. A historical climatological perspective would contribute to the study of medieval warfare by exploring relevant long-term climatic proxies as well as mapping weather conditions around the time of the campaign and battle. As an example, this study will investigate the weather during Duke William’s voyage to England in 1066. The study concludes with a discussion of the implications of these techniques for applying weather analyses to other historical events.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.233
Teacher spread0.220 · 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