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The Hudson Bay Lithospheric Experiment

2011· article· en· W1985506593 on OpenAlexaffabout
I. D. Bastow, J. M. Kendall, George Helffrich, David A. Thompson, James Wookey, Alex Brisbourne, David Hawthorn, David W. Eaton, D. B. Snyder

Bibliographic record

VenueAstronomy & Geophysics · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsGeological Survey of CanadaUniversity of Calgary
FundersNatural Environment Research CouncilSight Research UK
KeywordsPrecambrianGeologyBayLithosphereTectonicsEarth sciencePlate tectonicsSeismometerVolcanoPaleontologyHadeanArcticCrustSeismologyOceanography

Abstract

fetched live from OpenAlex

Geologists can usually interpret the rocks they encounter on Earth in the light of tectonic and volcanic processes presently operating at the plate boundaries. This approach works well for relatively young rocks (Phanerozoic: younger than 550 million years old), but for the older rocks that formed during Precambrian times (more than 550 million years old), the “plate tectonic” assumption must ultimately break down. Processes operating on the younger, hotter Earth would have been quite different to those we see today. Gathering detailed evidence preserved deep within the plates in the ancient cores of the continents (“shields”), is thus essential to our understanding of the early Earth. This can be achieved using data from dense seismograph networks, but building and maintaining them in remote areas is both logistically and financially challenging; innovative station and equipment designs are required to deliver the success enjoyed in gentler climes. The Hudson Bay Lithospheric Experiment (HuBLE), a recent UK-Canadian venture in Arctic Canada, has addressed these issues in order to place fundamental constraints on Earth structure beneath the Canadian Shield. The resulting data provide a tantalizing hint as to the processes that operated on the youthful Earth.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.184
Teacher spread0.171 · 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 designOther design
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

Citations9
Published2011
Admission routes2
Has abstractyes

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