MétaCan
Menu
Back to cohort
Record W4232994469 · doi:10.2523/86644-ms

Managing Health In Emergency Situations: Lessons Learned From Recent Events

2004· article· en· W4232994469 on OpenAlexaboutno aff
Caroline Minshell

Bibliographic record

VenueProceedings of SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCitationBusinessEmergency managementPublic relationsComputer scienceLibrary sciencePolitical science

Abstract

fetched live from OpenAlex

Managing Health In Emergency Situations. Lessons Learnt From Recent Events. Caroline Minshell Caroline Minshell BP Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. Paper Number: SPE-86644-MS https://doi.org/10.2118/86644-MS Published: March 29 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Minshell, Caroline. "Managing Health In Emergency Situations. Lessons Learnt From Recent Events.." Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. doi: https://doi.org/10.2118/86644-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability Search Advanced Search AbstractThe world is witnessing dramatic security events that heighten our awareness of these as individuals and nations and impact upon the business we conduct. Emergency planning is an important component of occupational health management and ever more apparent now. However, health often tends to be overlooked in business emergency and contingency plans. Little information can be found in the literature on emergency medical planning.BP has operations all over the globe often in remote and hostile environments, thereby creating ever more challenging issues for health management and emergency planning.Learning ObjectivesSharing BPs' processes for remote and emergency health planningSharing lessons learnt from BP's experience of recent eventsExploring health management in hostile and remote locationsAssessing health facilities and services including the consideration of their ability to stabilise medical and trauma conditions and integrate treatment with medical evacuation services and referral elsewhereThe importance of psychological support servicesConsideration of cultural differences and diverse infrastructuresEmergency Medical Planning & Lessons LearnedPoints to be coveredHow to prepare families for residence and work overseasMedically screen all families and vaccinate against infectious diseaseProvide health advice about destinationProvide first aid kits, training and travel items such as insect repellentProvide information on medical support in country, insurance processes and emergency numbes Keywords: hospital, regional occupational health advisor, evacuation, upstream oil & gas, eastern hemisphere, incident, emergency medical planning, caroline minshell, contingency planning, lesson learnt Subjects: HSSE & Social Responsibility Management, Health, Contingency planning and emergency response This content is only available via PDF. 2004. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.010
metaresearch head score (Gemma)0.020
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: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.005
Scholarly communication0.0050.013
Open science0.0020.005
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0050.002

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 head0.194
GPT teacher head0.382
Teacher spread0.188 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designTheoretical or conceptual · Other design
Domainnot available
GenreReview · Commentary

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 routes1
Has abstractyes

Explore more

Same venueProceedings of SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and ProductionSame topicRisk and Safety AnalysisFrench-language works237,207