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Record W7042977281

Regulation and policy working group

2018· other· en· W7042977281 on OpenAlexaboutno aff

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2018
Typeother
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsnot available
Fundersnot available
KeywordsSubmarine pipelineAbandonment (legal)Quarter (Canadian coin)Pipeline (software)Work (physics)Government (linguistics)Offshore drillingNorth seaContinental shelf
DOInot available

Abstract

fetched live from OpenAlex

The potential environmental impact of offshore platform disposal can be illustrated by both the numbers of platforms and the complexity of their abandonment options. Some 7,000 platforms are in place worldwide. In the US, approximately a quarter of the platforms are more than 25 years old and in sight of their end of service. In addition, 22,000 miles of pipeline are located on the Outer Continental Shelf (OCS) in the United States. There are more offshore platforms in the U.S. Gulf of Mexico than in any other single area in the world. It is estimated that between October 1995 and December 2000, approximately 665 of the nearly 3,800 existing structures will be removed. Couple this with the mammoth size, the vagaries of the ocean, and the levels of sometimes conflicting international and federal laws, and the magnitude of the challenge to protect the environment becomes clear. The Offshore International Newsletter (11/06/95) stated, {open_quotes}In three of the last four years, annual Gulf of Mexico platform removals have exceeded installations, a trend that will likely continue.{close_quotes} Between 100 and 150 platforms have been removed from the OCS each year for the past six or seven years. As increasing numbers of wells, pipelines, and platforms are decommissioned and disposed of, it is important that the relevant techniques, policies, and regulations be discussed and evaluated. The goal of this workshop is to facilitate and document this discussion in an open, objective, and inclusive way. Since U.S. practices and policies provide precedents for other countries, international participation is encouraged and anticipated.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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.

Study designNot applicable
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
Published2018
Admission routes1
Has abstractyes

Explore more

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