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Record W7051580488

Vigilant

2013· other· en· W7051580488 on OpenAlexaboutno aff

Bibliographic record

VenueThinkTech (Texas Tech University) · 2013
Typeother
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionTSG101Articular cartilage damageGestational periodLimitingParaphernalia
DOInot available

Abstract

fetched live from OpenAlex

Vigilant came not only late to the sail trade, but stayed late. While there were still ships being launched in the early 1920s, a result of the wartime shipping boom, most had short lives. Vigilant was the exception. Vigilant and another 4-masted schooner, Commodore, achieved local notoriety when they would “race” between Honolulu and Puget Sound in the twenties and thirties. Vigilant was generally considered the faster of the two, but the whole idea of sailing ships racing made too much good copy to not be repeated. In addition, there are many photographs of these two ships because the schooners worked so long into the twentieth century.
\nVigilant was a lumber schooner and remained in that trade throughout its career. Vigilant was an up-to-date sailer with steam winches, stockless anchors, and large carrying capacity. The square yard across its foremast is another characteristic of many latter-day west coast schooners. The photograph, 30c, obviously taken from an airplane, may be of Vigilant in Lake Union. The last photograph, 30d, shows to what depths old ships can sink—a pirates’ picnic.
\nVigilant hauled lumber up and down the Pacific coast and to Hawaii for U.S. owners (E. K. Wood Lumber Company) until 1940. During this time Vigilant was captained by Matt Peasley notable as the “Cappy Ricks” of Peter B. Kyne’s sea tales. In 1940 Vigilant came under Canadian ownership and was renamed City of Alberni. In 1946, City of Alberni burned.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.004
GPT teacher head0.149
Teacher spread0.144 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

Explore more

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