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Record W3181024882 · doi:10.1071/aj20156

International standardisation driving global competitiveness and sustainability of the oil and gas and future energy industries

2021· article· en· W3181024882 on OpenAlexaff
Matt Keys, Miranda Taylor

Bibliographic record

VenueThe APPEA Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsKensington Health
Fundersnot available
KeywordsStandardizationBusinessPetroleum industryProcurementSustainabilityAccountingEngineeringMarketingPolitical science

Abstract

fetched live from OpenAlex

The World Economic Forum has identified that the oil and gas (O&G) industry must lead the process of its own transformation by innovation and multistakeholder collaboration. The Capital Project Complexity initiative is an industry-wide, noncompetitive collaboration on standardisation and use of procurement specifications. Australia is now a major contributor to this collaboration which has brought together all the major O&G operators through the International Association of Oil & Gas Producers (IOGP) network and the standardisation bodies including International Organization for Standardization (ISO), American Petroleum Institute Standards, European Committee for Standardization, Gulf Cooperation Council Standardization Organization, Standardization Administration of China, Standards Australia (SA) and many more. The focus is on developing common international standards through an IOGP Standards-ISO/TC67 link and standardised equipment specifications linking to these standards through IOGP-JIP33. Australia contributes via SA’s mirror committee ME-92, which is now fully established with direct involvement in the ISO/TC67 9 subcommittee areas and 13 working groups covering 261 current and developing standards. In September 2020, the first of these standards, AS ISO 29001, was identically adopted as an Australian standard. With the Australian experts now ensuring ISO Standards will incorporate Australian industry expertise, knowledge and regulatory requirements where possible future revisions will enable them to be adopted as the next revision of the Australian standard. This industry-wide collaboration will ensure future project costs are optimised and safety enhanced through use of the global industry knowledge while also reducing the need to write local standards. This study describes Australia’s strategy being pursued to align with the global industry. It also provides information on how this network is supporting the development of knowledge transfer to the decommissioning and new energy industries that will form Australia’s future.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.172

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.003
GPT teacher head0.196
Teacher spread0.193 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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