Implied threats of the Red Sea crisis to global maritime transport: amplified carbon emissions and possible carbon pricing dysfunction
Bibliographic record
Abstract
Abstract Recent military acts in the Red Sea and Gulf of Aden are forcing merchant ships to reroute, thereby driving up international shipping rates, prolonging delivery dates, and causing additional greenhouse gas emissions. Utilizing the European Union (EU) Monitoring, Reporting, and Verification emissions database and real time Automatic Identification System data, this study conducted frequency analysis and causative investigation on container ships circumnavigating the Cape of Good Hope. The findings indicate that the current policy framework under the EU Emissions Trading System (EU-ETS) poses a higher risk of carbon leakage, particularly for medium and small-sized container ships, thereby undermining the effectiveness of the nascent EU maritime carbon pricing. If the crisis continues, combined with anticipated tighter emission regulations, this risk is expected to escalate. International maritime policy administrators should make timely adjustments in response to the chain reactions caused by war, enhancing the robustness of cross-regional carbon pricing.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".