The utility of historical records for hazard analysis in an area of marginal cyclone influence
Bibliographic record
Abstract
Abstract Shark Bay Marine Park is a UNESCO World Heritage Property located in a region of marginal tropical cyclone influence. Sustainable management of this unique environment as the climate changes requires a quantified understanding of its vulnerability to natural hazards. Here, we outline a structured analysis of novel historical archive information that has uncovered reports of an extreme storm surge associated with a Tropical Cyclone in 1921 that generated remarkable overland flow which left fish and sharks stranded up to 9.66 km (6 miles) inland. Weighted information from historical archives is placed in a new framework and provide inputs to modelling of this event which improves the understanding of its magnitude and furnishes records of the impacts of what occurred on that day and notably also in the years following. The suite of plausible tracks that reproduce the historical data contextualise the storm as a marginal Category 4 or 5 storm and its return interval as equivalent or slightly greater than the current local planning level for coastal flooding in the region. The outcome underscores the global importance of examining the probable maximum event for risk management in areas of marginal cyclone influence where vulnerable ecosystems or vital regional infrastructure of key economic importance are located, and the need to factor in TC risk in marine conservation and planning in the Shark Bay World Heritage Property.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".