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Record W1906907142 · doi:10.1029/2002gc000449

Quantitative bedrock geology of Alaska and Canada

2003· article· en· W1906907142 on OpenAlexaboutno aff
Bernhard Peucker‐Ehrenbrink, Mark W. Miller

Bibliographic record

VenueGeochemistry Geophysics Geosystems · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsGeologyBedrockmyrLithologyUltramafic rockMetamorphic rockPrecambrianSedimentary rockGeological surveyVolcanic rockIgneous rockGeochemistryVolcanoGeologic mapGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

We quantitatively analyze the area‐age distribution of sedimentary, igneous, and metamorphic bedrock on the basis of data from the most recent geologic maps of Alaska [ Beikman , 1980 ] (1:2,500,000) and Canada [ Douglas , 1969 ] (updated; 1:5,000,000), made available in digital form by the U.S. Geologic Survey and the Geologic Survey of Canada (National Resources Canada), respectively. Sediments cover 72.9% and 52.4% of the surface of Alaska and Canada. Volcanic rocks comprise 11.6% and 6% of the surface area in Alaska and Canada, respectively, whereas intrusive rocks cover 6.6% and 24% of the surface, respectively. Ultramafic rocks account for 0.20% and 0.08% of the bedrock area, whereas metamorphic rocks cover 3.4% and 16.1%. The average ages of major lithologic units, weighted according to bedrock area, are significantly younger in Alaska than in Canada: marine sediments (stratigraphic age of 206 Myr in Alaska versus 599 Myr in Canada), continental sediments (stratigraphic age of 81 Myr versus 150 Myr), volcanic rocks (126 Myr versus 1377 Myr), intrusive rocks (114 Myr versus 2109 Myr), ultramafic rocks (261 Myr versus 874 Myr), and metamorphic rocks (474 Myr versus 2545 Myr). This age difference reflects the contrast between the young active margin influence on the geology of Alaska and the old cratonic nature of much of the bedrock exposed in Canada. Glacial erosion, and the resulting exposure of Precambrian bedrock, primarily in Canada, contributes to this age contrast. The average temporal and spatial resolution of the digital data is sufficiently high to perform age‐area analyses on individual river basins larger than ∼20,000 km 2 and to evaluate the relationship between bedrock geology and river chemistry.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.719

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)0.0000.000

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations20
Published2003
Admission routes1
Has abstractyes

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