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Record W2325885316 · doi:10.3189/2014aog68a042

Deep ice-core drilling performance and experience at NEEM, Greenland

2014· article· en· W2325885316 on OpenAlexfundno aff
Trevor Popp, Steffen Bo Hansen, Simon G. Sheldon, Christian Panton

Bibliographic record

VenueAnnals of Glaciology · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersNatural Environment Research CouncilCentre National de la Recherche ScientifiqueKorea Polar Research InstituteAgence Nationale de la RechercheNederlandse Organisatie voor Wetenschappelijk OnderzoekInstitut Polaire Français Paul Emile VictorNatural Resources CanadaFonds Wetenschappelijk OnderzoekNational Institute of Polar ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungOffice of Polar ProgramsFonds De La Recherche Scientifique - FNRSUniversity of BernNational Science Foundation
KeywordsDrillingDrillGeologyBoreholeIce corePenetration rateRate of penetrationMud loggingDrilling fluidDrilling engineeringPetroleum engineeringPaleontologyMechanical engineeringOceanographyEngineering

Abstract

fetched live from OpenAlex

Abstract The NEEM deep ice-core drilling in northwest Greenland was completed in summer 2010 after three seasons, which included establishing all drilling infrastructure. Normal drilling operations in the main borehole were declared terminated at 2537.36 m below the surface, when further penetration was stopped by a stone embedded in the ice in the path of the drill head. The design and implementation of the drilling operation strongly resembled the NGRIP drilling program. The NEEM drill was an extended version of the Hans Tausen (HT) drill, with specific modifications to optimize its use with the highly viscous Estisol-240/Coasol drill fluid used at NEEM. Modification to the drill and its performance in the new drilling fluid was largely satisfactory and successful. Throughout the drilling, special consideration was given to the way chips were transported and collected in a new chip chamber, including the consequences of drilling a larger borehole diameter than with previous drill operations that used the HT family of drills. The problems normally associated with warm ice drilling near the base of an ice sheet were largely absent at NEEM.

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 score0.027
Threshold uncertainty score0.430

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 head0.064
GPT teacher head0.269
Teacher spread0.204 · 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

Citations29
Published2014
Admission routes1
Has abstractyes

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