MétaCan
Menu
Back to cohort
Record W4235065219 · doi:10.2523/94416-ms

Upstream Onshore Oil and Gas Fatalities: A Review of OSHA's Database and Strategic Direction for Reducing Fatal Incidents

2005· review· en· W4235065219 on OpenAlexaff
Charles Curlee, Steve Brouillard, Michael Marshall, Thomas Knode, S. Smith

Bibliographic record

VenueProceedings of SPE/EPA/DOE Exploration and Production Environmental Conference · 2005
Typereview
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsUpstream (networking)Petroleum industryNear missHazardous wasteFossil fuelEngineeringTransport engineeringDatabaseBusinessForensic engineeringOperations managementWaste managementComputer scienceEnvironmental engineeringTelecommunications

Abstract

fetched live from OpenAlex

According to the OSHA database for the period from 1997 through 2003, one fatality occurred every 10 days in the U.S. upstream (E&P) oil and gas industry. To determine trends and provide insights into the safety failures, as well as potential interventions to eliminate the high frequency of fatal incidents, the seven years of OSHA data were reviewed. This data encompasses over 250 fatalities from the four principal SIC categories that comprise the onshore upstream oil & gas exploration and production industry. Data were sorted initially by region, well drilling or field servicing, rig type, and event. Further analysis was conducted by a diverse team of industry professionals, including representatives from operating companies, well drilling and servicing companies, and industry trade associations. Particular focus was directed at accident type, equipment type and well site location in an attempt to identify causal factors from the limited incident descriptions contained in the OSHA database.The resulting analysis showed nearly half of all fatalities (47%) resulted from

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)0.012
metaresearch head score (Gemma)0.025
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: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0190.020
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.229
GPT teacher head0.453
Teacher spread0.224 · 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
GenreReview

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

Citations11
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPE/EPA/DOE Exploration and Production Environmental ConferenceSame topicOccupational Health and Safety ResearchFrench-language works237,207