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Record W4410577144 · doi:10.1071/ep24225

Development of Australia’s National Action List for offshore CCS

2025· article· en· W4410577144 on OpenAlexaff
David J. Midgley, Linda Stalker, Andrew J. Ross, S. Sestak, Sharon E. Hook, Emma Crooke, Charles Jenkins

Bibliographic record

VenueAustralian Energy Producers journal. · 2025
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsKensington Health
Fundersnot available
KeywordsSubmarine pipelineAction (physics)Political scienceEnvironmental scienceOceanographyGeology

Abstract

fetched live from OpenAlex

A review of international and domestic policy and legislative requirements by the Department of Climate Change, Energy, the Environment and Water (DCCEEW) identified several requirements for implementation of the 1996 Protocol to the Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter 1972 (the London Protocol) for offshore storage of CO2 in Australian waters, including a National Action List (NAL). The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has been contracted by DCCEEW to undertake a joint program of work on Australia’s offshore carbon capture and storage (CCS) NAL. A literature review has identified components found within CO2 streams, their concentrations and potential impacts to environmental and/or human health. Benchmarking CO2 specifications has been possible by reviewing a wide range of CO2 storage project specifications and shows how these have evolved as CO2 providers have changed and capture technologies have advanced. Appraisal of the potential risks of each incidental associated substance (IAS) within CO2 streams was then considered including assessment of toxicity, pathway to harm, risk to workers and the environment. This has resulted in development of an interim NAL which specifies the levels of allowed contaminants within CO2 streams for offshore sequestration. DCCEEW published the Interim NAL in February 2024. Further work has been ongoing, including incorporating industry feedback on the interim NAL where relevant on an offshore CCS NAL with upper and lower levels of IAS. This presentation will discuss CSIRO’s contribution to the technical aspects of the development and evolution of the interim NAL.

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)0.013
metaresearch head score (Gemma)0.014
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.109
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0040.001
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0300.015

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 head0.051
GPT teacher head0.305
Teacher spread0.254 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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