Comparison of measured and modeled speed of sound in the challenger deep
Bibliographic record
Abstract
Echo sounding and acoustic propagation in the hadal zone (depths below 6 km) rely on models of sound speed that suffer from uncertainty due to a paucity of measurements at those depths. In order to assess models of sound speed in deep water, and to provide additional measurements, the Deep Acoustic Lander, a passive acoustic profiler, was deployed into the Mariana Trench from the RV Pressure Drop in April 2021. The Deep Acoustic Lander houses an array of hydrophones along with an AML Scientific CTD and AML MinosX sound speed meter. Pressure, temperature and salinity data measured by the CTD were used to inform some of the most commonly used sound speed models. The modeled sound speed was then compared with direct measurements of the speed of sound in the hadal zone to depths beyond 10 000 m. The goodness of fit between each model and the direct measurements was then compared to assess the performance of each model in 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".