Bibliographic record
Abstract
The area of the ocean, as derived from a new analysis of two digital data sets, is near to 362.5 Mm2 (1Mm2 = 106 km2). The decimal digit is meaningful: uncertainty is about ±0.1 Mm2 or ±0.03%. Although it is impractical to quantify their dominant errors precisely, the ocean areas presented in both of the canonical sources are significantly more uncertain. The often-quoted figure of 361 Mm2 probably derives from the work of Kossinna in 1921 and represents the ocean without the ice shelves and floating glacier tongues, which have an area at present of 1.561 Mm2. The often-quoted figure of 362 Mm2 probably derives from the work of Menard and Smith in 1966 and includes the ice shelves, as it should for the purpose of converting masses of cryospheric or terrestrial water to sea-level equivalent units. However, when Kossinna's estimate is corrected by adding the ice shelves, the two canonical estimates are seen to be inconsistent. The discrepancy implies that measurement errors are much larger than estimated in one source or in both, but Kossinna's estimate, when corrected, agrees much more closely with the modern digital estimates than does the Menard-Smith estimate.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".