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Record W1919802383

Arctic risk: a discussion of the possible outcomes of two disaster scenarios

2015· article· en· W1919802383 on OpenAlexaboutno aff
Ben Lishman

Bibliographic record

VenueResearch Open (London South Bank University) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticGeographyPolitical scienceOceanographyGeology
DOInot available

Abstract

fetched live from OpenAlex

We believe that the risks associated with Arctic development often involve the overlap of disciplines \nand sectors. Based on this belief, we organized an Arctic Risk Scenario meeting on the 12th September \n2014. Invited participants worked through two Arctic disaster scenarios. The scenarios chosen were: \n(1) a cruise ship sinking off north east Spitzbergen, and (2) an oil well blowout in the Kara sea. \nParticipants came from the oil and gas industry, shipping, law, politics, humanitarian agencies and \nacademia: one aim of the meeting was to bring together diverse perspectives on the Arctic. \nTwo invited speakers presented relevant background. Dr Nataly Marchenko (The University Centre in \nSvalbard (UNIS), and author of the book “Russian Arctic Seas”) discussed a series of recent Arctic \nshipping near8disasters. Dr Rocky Taylor (C8Core, St John’s, Newfoundland, Canada) discussed the \ncomplexities of oil exploration and production in Arctic seas, again based on a number of reference \nevents. The rest of the meeting was held under the Chatham House Rule. Diverse views were \nexpressed, and in this document we highlight topics of broad consensus and areas of disagreement. \nThis document highlights observations and outcomes from the meeting which may affect the UK’s \nongoing interests in Arctic development. It was submitted to, and published by, the UK House of Lords \nArctic Committee, under their 2014 call for evidence.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.002
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 head0.114
GPT teacher head0.392
Teacher spread0.278 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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