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Record W4385869838 · doi:10.59962/9780774857918

Ocean of Destiny

2007· book· sk· W4385869838 on OpenAlexaboutno aff
J. Arthur Lower

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2007
Typebook
Languagesk
FieldSocial Sciences
TopicMaritime Security and History
Canadian institutionsnot available
Fundersnot available
KeywordsDestiny (ISS module)OceanographyGeologyAstronomyPhysics

Abstract

fetched live from OpenAlex

The modern history of the North Pacific began five hundred years ago when Europeans sailed into the ocean for the first time. This discovery shaped the destinies of seven countries that now rim its Asiatic and North American shores: Russia, China, Japan, North Korea, South Korea, the United States, and Canada. Their history is an exciting epic of discovery -- the great expeditions of Marco Polo, Drake, and Magellan; the quest for the spices of Cathay; the early days of the fur trade, the gold rush, and the long treks westward across North America to first establish Canadian and American possessions on the Pacific shore. Rivalry and confrontation were part of this epic. From the sixteenth to the nineteenth century European powers contested for the riches of the East and the West, the wealth of the ocean, and territory to sate colonial ambitions. Since that time full-blooded conflicts developed between Asian states and between Asia and the Western powers. As a major trading power in the Pacific with no tradition of territorial expansion, and as a respected peacekeeper, Canada is in a unique position to view the history of the Pacific impartially. This survey is doubly valuable, not only as the first history of the North Pacific dealing with the concurrent events in the East and West, but also as a history reflecting Canada's international outlook.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.008
Scholarly communication0.0080.004
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0280.005

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 head0.017
GPT teacher head0.198
Teacher spread0.181 · 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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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Same venueUniversity of British Columbia Press eBooksSame topicMaritime Security and HistoryFrench-language works237,207