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Record W1978117518 · doi:10.2118/168485-ms

Leveraging Sustainability in the Oil and Gas Supply Chain

2014· article· en· W1978117518 on OpenAlex
Jan Dell, Virginia Hart

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE International Conference on Health, Safety, and Environment · 2014
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsSupply chainSustainabilityBusinessSupply chain managementScheduleSupply chain risk managementEnvironmental economicsQuality (philosophy)Production (economics)Corporate governanceIndustrial organizationProcess managementFinanceMarketingService managementComputer scienceEconomics

Abstract

fetched live from OpenAlex

Abstract Successful project execution and business operations depend on the performance of a strong supply chain. Weak links in a supply chain may be caused by a range of drivers beyond the safety, financial, quality and schedule indicators that have historically been considered in supplier selection and management. Sustainability aspects including environmental, social and governance issues can weaken supplier performance by causing lost production, supply interruptions, schedule delays, material inefficiencies, price increases, safety impairment, regulatory violations, employee issues and community resentment. This paper describes elements of ConocoPhillips’ Supply Chain Sustainability program as expanded in 2013 to support the improvement of our project execution and operations management through strengthening our supply chain on sustainability drivers that impact our business. A summary of the benefits of collaboration on sustainability issues to both oil and gas companies and suppliers is presented.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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