Spectral solar radiation over and under sea ice from remotely operated vehicle (ROV) surveys during the ARTofMELT2023 expedition
Bibliographic record
Abstract
Solar radiation over and under drifting sea ice was measured using RAMSES hyper-spectral radiometers (TriOS) mounted on the remotely operated vehicle (ROV) during the ARTofMELT2023 expedition in May and June 2023. All data are given in full spectral resolution interpolated to 1.0 nm, integrated over the entire wavelength range (broadband, total: 320 to 950 nm), and integrated over the photosynthetically active radiation wavelength range (PAR: 400 to 700 nm). Two sensors were mounted on the ROV, an irradiance sensor (transmitted solar irradiance, ACC: Advanced-Cosine-Collector) for energy budget calculations and a radiance sensor (transmitted solar radiance, ARC: Advanced-Radiance-Collector with a 7° opening angle) to obtain high-resolution spatial variability. One additional radiometer was installed on - board the ship for reference measurements (incident solar irradiance, ACC). This is a raw data set, including all recorded spectra without any selection. Along with the radiation measurements, ROV positions were obtained from an acoustic Long Base Line (LBL) positioning system (LinkQuest Pinpoint). ROV depth was measured by a pressure sensor (Keller A-21Y, Keller AG). All times are given in Universal Coordinated Time (UTC).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".