Decompression procedures for transfer under pressure (‘TUP’) diving
Bibliographic record
Abstract
Background: There is an increasing interest in ‘transfer under pressure’ (TUP) decompression in commercial diving, bridging traditional surface-oriented diving and saturation diving. In TUP diving the diver is surfaced in a closed bell and transferred isobarically to a pressure chamber for final decompression to surface pressure. Methods: Tables for air diving and air and oxygen decompression have been compared for total decompression time (TDT), oxygen breathing time as well as high and low gradient factors (GF high and low). These have been considered surrogate outcome measures of estimated decompression sickness probability (PDCS). Results: Six decompression tables from DadCoDat (DCD, The Netherlands), Defence and Civil Institute of Environmental Medicine (DCIEM, Canada), Comex MT92 tables, (France) and the United States Navy (USN) have been compared. In general, USN and DCD procedures advised longer TDT and oxygen breathing time and had a lower GF high compared to MT92 and DCIEM tables. GF low was significantly higher in USN procedures compared to DCD and one of the MT92 tables due to a shallower first stop in many USN profiles compared to the two others. Allowance and restrictions for repetitive diving varied extensively between the six procedures. While USN procedures have been risk-assessed by probabilistic models, no detailed documentation is available for any of the tables regarding validation in experimental and operational diving. Conclusions: Absence of experimental testing of the candidate tables precludes firm conclusions regarding differences in PDCS. All candidate tables are recognised internationally as well as within their national jurisdictions, and final decisions on procedure preference may depend on factors other than estimated PDCS. USN and DCD procedures would be expected to have lower PDCS than MT92 and DCIEM procedures, but the magnitude of these differences is not known.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".