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Record W1975039298 · doi:10.1029/2002eo000302

Piston cores improve understanding of deep Arctic Ocean

2002· article· en· W1975039298 on OpenAlexaboutno aff
David L. Clark, Arthur Grantz

Bibliographic record

VenueEos · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyCoringCretaceousArcticCenozoicPaleontologyDeep seaDrillingOceanic basinPaleogeneOceanographyCanada BasinStructural basin

Abstract

fetched live from OpenAlex

Recent proposals for deep Arctic Ocean drilling [COMPLEX, 2000; JOIDES, 2001] are significant steps toward an eventual understanding of the geologic framework, plate kinematics, and Cretaceous and Cenozoic environmental history of the north polar ocean. Because the proposals are subject to a variety of fiscal uncertainties, however, deep drilling in the ice‐covered ocean could be years away from initiation. However, even in the absence of drilling, significant data concerning the geologic framework and Cretaceous‐to‐Eocene and late Cenozoic paleoenvironment of the Arctic Ocean basin have developed from piston cores collected from crests and flanks of Arctic Ocean ridges. While deep drilling is needed to test and amplify the commonly incomplete piston core record, some piston cores already have acquired firm data on lithology age, and paleoenvironment of Cambrian‐to‐Tertiary bedrock in parts of the Alpha, North wind, and Lomonosov Ridges (Figure l), and additional piston coring may be the best choice for immediate additional Arctic Ocean research.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.056
GPT teacher head0.199
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; 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 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

Citations18
Published2002
Admission routes1
Has abstractyes

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