Why this work is in the frame
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Bibliographic record
Abstract
Abstract A processing methodology for computation of accurate salinity from measurements with an underway CTD (UCTD) is presented. The UCTD is a rapidly profiling sensor package lacking a pump that relies on instrument motion to produce flow through the conductivity cell. With variable instrument descent rate, the flow through the cell is not constant, and this has important implications for the processing. As expected, the misalignment of the raw temperature and conductivity is found to be a function of the instrument descent rate. Application of a constant temporal advance of conductivity or temperature as is done with pumped CTDs is shown to produce unacceptable salinity spiking. With the descent rate of the UCTD reaching upwards of 4 dbar s−1, the effect of viscous heating of the thermistor is shown to produce a significant salinity error of up to 0.005 psu, and a correction based on previous laboratory work is applied. Correction of the error due to the thermal mass of the conductivity cell is achieved using a previously developed methodology with the correction parameters varying with instrument descent rate. Comparison of salinity from the UCTD with that from a standard shipboard, pumped CTD in side-by-side deployments indicates that the processed UCTD salinity is accurate to better than 0.01 psu.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it