The Use of the International Hydrographic Organisation's 'Standards for Hydrographic Surveys' As a Measure of Depth Accuracy in Continental Shelf Determinations
Bibliographic record
Abstract
Article 76 of UNCLOS requires the determination of depths of 2,500m to establish the position of one of the two alternative components of the Outer Constraint to the Continental Shelf. Recognising the water depth’s possible role, the Guidelines produced by the Commission on the Limits of the Continental Shelf (CLCS) specify the types of depth-measuring instrumentation that can be used, the types of analysis to transform bathymetry data into a bathymetric model, and the type of database and supporting information to be provided. Included in the latter is the requirement to provide A priori or a posteriori estimates of random and systematic errors’, where a priori errors may be calculated using the International Hydrographic Organisation's (IHO's) S44 Standard for Hydrographic Surveys. Having the CLCS refer to this internationally accepted standard as the most appropriate for UNCLOS purposes imposes a responsibility on the IHO to ensure that S44 does provide an appropriate, up to date and achievable standard for 2,500m water depths. This paper shows how S44 could be revised to make it fully suitable for this new task, one that for which it was not originally designed . S44 defines total error as the Root Sum of Squares (RSS) of the constant and variable depth errors. Marine areas are divided into zones according to their use by surface shipping, and a table provides the values to be substituted in the RSS equation for each area. While this approach has proven useful for transportation purposes, it is not necessarily applicable to deep-water contours, in that it does not take into account the magnitude and impact of the many factors that influence the uncertainty of location of deep water contours. These differ greatly in their magnitude and influence as the sea floor deepens beyond navigation depths, and are explained in this paper. We conclude with a firm suggestion to the IHO to undertake production of a new edition of S44 and include information on how it can be expanded to become more applicable to deep water.
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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 | 0.024 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".