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Record W1977663665 · doi:10.2118/86734-ms

A Multimedia Approach to Incident Dissemination

2004· article· en· W1977663665 on OpenAlexaffabout
Keith Eslinger

Bibliographic record

VenueSPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsDisseminationPresentation (obstetrics)Key (lock)Shell (structure)Computer scienceMultimediaAudience participationEmergency responseEvent (particle physics)TelecommunicationsEngineeringComputer securityMedicineMedical emergency

Abstract

fetched live from OpenAlex

Abstract On Wednesday March 12, 2003 Shell Canada Limited's Caroline Complex experienced an emergency incident due to a release of gas containing hydrogen sulphide. Because of the large area affected – more than 400 km2 and 790 residents, Shell needed a tool to disseminate the cause, the actions taken, and the barriers / recoveries in place. Communicating these issues in an easy to understand manner was key to regaining trust with the public and regulatory bodies. The Multimedia presentation was selected, and initially presented at a workshop attended by residents, other companies, and local regulators. The video was also formatted and distributed to all interested stakeholders, including other Shell operations. This paper deals with the creation of, and response to, the multimedia presentation. As a pilot project for Shell Caroline, the presentation has been very successful, and the technology will be used in future to disseminate incidents internally and externally, as well as for public consultation of new projects.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0070.005
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0510.006

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 head0.096
GPT teacher head0.357
Teacher spread0.260 · 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 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
Published2004
Admission routes2
Has abstractyes

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