D.4.2.1. Guidance document on implementation of Monitoring and Reporting of MRV
Bibliographic record
Abstract
The legislative process of the amendment of the Regulation on Monitoring, Reporting, and Verification of CO2 emissions from ships (EU-MRV, Regulation 2015/757) was initially motivated by the administrative burden for the shipping companies obligated to report under both the EU-MRV and the International Maritime Organization Data Collection System (IMO DCS). However, following the momentum set by the European Green Deal, the amendment of the EU-MRV will also include decarbonization goals and moves towards the inclusion of the shipping sector into the Union’s Emission Trading System. The shipowners will need to adjust their way of business by investing in low carbon fuels to avoid high costs per carbon unit. This report aims to review the EU MRV amendment process, some parts of the European Green Deal, and its effect on EU flagged ships. Also, it provides an opinion on future decarbonization trends according to IMO and EU goals for 2030.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.024 | 0.008 |
| Insufficient payload (model declined to judge) | 0.020 | 0.028 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".