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CARBONIFEROUS NON‐MARINE SOURCE ROCKS FROM SPITSBERGEN AND BJØRNØYA: COMPARISON WITH THE WESTERN ARCTIC

2010· article· en· W2136721922 on OpenAlexaboutno aff
Jan Hendrik van Koeverden, Dag A. Karlsen, Kristian Backer-Owe

Bibliographic record

VenueJournal of Petroleum Geology · 2010
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyCarboniferousArcticArchipelagoSource rockSverdrupOceanographyStructural basinContext (archaeology)PaleontologyGeochemistry

Abstract

fetched live from OpenAlex

In this paper, we demonstrate that Carboniferous coaly and lacustrine strata have significant liquid hydrocarbon potential in an area extending from the Norwegian Barents Sea in the east to the Canadian Arctic in the west. Organic geochemical analyses were conducted on seven coals and coaly shales from the islands of Spitsbergen (Svalbard archipelago) and Bjørnøya (Norwegian Barents Sea). The results were interpreted in the context of published data from the two areas, and of time‐equivalent non‐marine successions on the Finnmark Platform (Norwegian Barents Sea), East Greenland, and the Sverdrup Basin (Canadian Arctic). In each of these areas, a warm and humid climate, together with the onset of rifting on the northern Pangea margin, facilitated the deposition and preservation of organic‐rich non‐marine sediments on a regional scale. All of the sediments have an elevated content of liptinitic macerals, dominated by alginite or sporinite. In the studied areas, the prolific younger source rocks which may be common in adjacent regions are often immature or absent. The identification of Carboniferous terrestrial strata with source rock potential may therefore enhance the petroleum potential of the studied regions.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.517
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations57
Published2010
Admission routes1
Has abstractyes

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