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Record W3167902223

Los canadienses y el Día D

2021· article· es· W3167902223 on OpenAlexaboutno aff
Terry Copp

Bibliographic record

VenueVirtual Defense Library (Ministerio de Defensa) · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicHistory and International Relations
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

La contribucion de Canada al esfuerzo aliado fue verdaderamente sorprendente. Al final de la guerra, un pais de 11 000 000 de habitantes habia movilizado a mas de 1 000 000 de soldados, entre los que se incluian 50 000 mujeres y un 41,5 % de la poblacion masculina entre los dieciocho y cuarenta y cinco anos. De estos, el 85 % eran voluntarios. Se distribuyeron entre el Ejercito de Tierra, que fue el que desplego el mayor numero de efectivos, mas de 700 000, la Fuerza Aerea, con otros 222 501, y la Royal Canadian Navy, con otros 99 407. La primera batalla de relevancia en la que participaron tuvo lugar en agosto de 1942, cuando un escuadron naval de 237 buques y lanchas de desembarco, asi como 16 dragaminas, alcanzo la costa de Francia a la altura de Dieppe con mas de 6000 efectivos. El asalto se confio a batallones de infanteria que, tras dos meses de entrenamiento intensivo, habian sido imbuidos en un espiritu muy agresivo. Para superar las trincheras alemanas emplearian una combinacion de tacticas de comando, una moral muy elevada y el factor sorpresa. Ademas, como iban a carecer de artilleria, los soldados de esta arma que desembarcaron habian sido entrenados para emplear las piezas que pudieran capturar al enemigo.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.193
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0110.004
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0390.005

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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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