Near-bottom temperature data obtained from Current and Pressure-recording Inverted Echo Sounders (CPIES) and processed HYCOM data near the Chukchi slope (version 2)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Quasi-seasonal and quasi-monthly variations of near-bottom temperature were observed using Current and Pressure-recording Inverted Echo Sounders (CPIES) deployed on the slope between the Canada basin and the Chukchi shelf from August 2018 to July 2020.They were equipped with a 4930R ZPulse Doppler current sensor positioned approximately 51 m above the seafloor, which measured near-bottom current and temperature. Among the variables CPIES measured, we used the near-bottom temperature, the resolution and accuracy of which are 0.01°C and 0.1°C, respectively. We also used temperature, velocity, and sea surface height data from the Hybrid Coordinate Ocean Model (HYCOM). We collected outputs from the HYCOM + NCODA Global 1/12° GOFS 3.1 41-layer analysis (GLBy0.08 Experiment 93.0). It has a horizontal resolution of 0.08° × 0.04° (zonal and meridional, respectively) and a temporal resolution of 3 h.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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