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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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.754

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 head0.051
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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