Collaborative Seismic Environment Plan (CSEP) project – a long-term, consistent, consortium-based approach to environmental approvals
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.
Bibliographic record
Abstract
The Collaborative Seismic Environment Plan (CSEP) project was formed in 2018 by NERA (National Energy Resources Australia) and an industry consortium of marine seismic acquisition operators and exploration titleholders. Using a collaborative approach, the vision of the CSEP project was to streamline seismic survey environment plan preparation, submission and assessment by the regulator (National Offshore Petroleum Environmental and Safety Authority, NOPSEMA), with an emphasis on mutually agreed protocols with commercial fishers operating within the CSEP Operational Area. Stakeholder consultation undertaken during Environmental Plan (EP) preparation was identified by the consortium as a principal cause for concern and a common reason for unsuccessful EP submissions. The CSEP project has achieved the project’s vision through: A Commercial Fishing Industry Adjustment Protocol to provide a standardised, evidence-based process to assess and provide monetary adjustment to commercial fishers for loss of catch, displacement and gear loss/damage; an Operational Protocol to provide guidance regarding improved communications with commercial fishers, including the spatial and temporal repetition and advanced notifications of seismic activities; a single overarching approvals framework for seismic activities within the CSEP Operational Area; a consistent assessment of environmental receptors, potential impacts, and management controls for seismic activities; and Improved understanding of potential cumulative impacts of seismic activities across the CSEP Operational Area. The CSEP project is an example of best practice stakeholder consultation that can be applied to offshore oil and gas and renewable energy activities.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it