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Record W6999385643

1790 – Carte de la Mer Pacifiquen, du Nord, contenant la Cote Nord-Est D’Aise et la Cote Nord-Ouest D’Amérique reconnues en 1778 et 79 par le Cap. Cook, et plus particulierement encore en 1788 et 89 par le Cap. Jean Meares

2017· article· en· W6999385643 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons - CSUMB (California State University, Monterey Bay) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsnot available
Fundersnot available
KeywordsPortuguesePacific oceanSoutheast asiaToponymy
DOInot available

Abstract

fetched live from OpenAlex

A map depicting the northern regions of the Pacific Ocean by Jean Meares. The map reflects areas from Central Asia to Baja California but mainly focuses on the tracks of various explorers throughout the Northwest, Alaska, Canada, Hawaii, Western Pacific and Southeast Asia. The map traces routes taken by Captain James Cook in his third and final voyage between 1778 and 1779. The map also traces the courses taken in 1788 and 1789 by ships owned by British citizen, Captain Jean Meares who was perceived by some to be less than scrupulous in his words and deeds. Cook’s experience in the Pacific brought to light that there was an opportunity to make a fortune in the fur trade. This ultimately lead to legitimate and questionable fur trading by competing European interests, largely with the Chinese. Meares registered his ships in Macau, a Portuguese colony in China. The ships bore Portuguese names, “Iphigenia Nubiana” and “Felice Adventurero,” and were licensed under the Portuguese flag thus allowing Meares to circumvent the requirement that British traders be licensed by and pay duties to the East India Company. The fact that this is a French map suggests that it was most likely published in 1790 in a four volume French version of his English publication, “Voyages Made in the Years 1788 and 1789.” Meares included maps and plats in volume 4 of the French edition.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDigital Commons - CSUMB (California State University, Monterey Bay)Same topicMigration, Health, Geopolitics, Historical GeographyFrench-language works237,207