SkiMonkey mounted MicroCAT CTD data from around Prince Edward Island on SA Agulhas II Voyage 024, April 2017
Bibliographic record
Abstract
With the declaration on 9 April 2013 of the Prince Edward Islands (PEIs) as South Africa’s first offshore Marine Protected Area (MPA), the outcomes of this cruise will further contribute toward an integrated view and a better understanding of the functioning of the combined island/marine PEI ecosystem.This accession contains raw and processed SkiMonkey mounted SBE-37 MicroCAT CTD data collected from part of the Marion Island Relief Voyage on the SA Agulhas II Voyage 024. At each station the SkiMonkey III towed camera system, with the MicroCAT CTD attached, was deployed off the stern of the ship, from the plankton towing winch at a speed of 1 m/s until contact with the seafloor was made. Once on the seafloor, the system was towed behind the vessel at a speed of 1 knot for approximately 20 minutes. Following this, the system was retrieved and the data were downloaded and backed-up appropriately. Note that latitude and longitude information were only recorded at two points per station, when the system touched down on the seafloor and when it was retrieved from the seafloor (i.e. Start_Lat_DD, Start_Lon_DD, End_Lat_DD, End_Lon_DD). The download is divided into station level folders, within which the user can find ReadME documents describing the variables recorded in the data, a _StationLevelData sheet describing the instrument deployment, a _RawData file with data extracted as is from the instrument, and a _CleanData file with processed data as described in the metadata lineage statement.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".