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Record W2472041233 · doi:10.1080/00934690.2016.1184930

Second World War bomb craters and the archaeology of Allied air attacks in the forests of the Normandie-Maine National Park, NW France

2016· article· en· W2472041233 on OpenAlexaff
David Capps Tunwell, David G. Passmore, Stephan Harrison

Bibliographic record

VenueJournal of Field Archaeology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsUniversity of Toronto
FundersRégion Normandie
KeywordsWorld War IIGermanArchaeologyCombatantNational parkImpact craterStrategic bombingPopulationGeographyHistory

Abstract

fetched live from OpenAlex

Well-preserved bomb craters in the forests of central Normandy, NW France, constitute archaeological legacies of combat inland from the D-Day beachheads that greatly extend the inventory of Second World War conflict landscapes in northwest Europe. Field survey and analysis of German and Allied documents demonstrates that bombscapes in the Forêt domaniale des Andaines and Forêt domaniale d'Ecouves reflect US Ninth Army Air Force attacks on a German fuel depot and radar installation, respectively, during June-August, 1944. One hundred and thirty-six craters are mapped, described and linked to specific air raids, bomb types and, for one raid on the 13th June, six specific participating aircraft and aircrews. These landscapes echo the impact of widespread tactical bombing against targets close to civilian population centers, and in some cases employing civilian and PoW labor. They are therefore well-placed to contribute to wider heritage narratives around the non-combatant experience of aerial warfare in WWII.

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 score0.303
Threshold uncertainty score0.603

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.244
Teacher spread0.231 · 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

Citations29
Published2016
Admission routes1
Has abstractyes

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