Autonomous station for meteo-oceanographic data acquisition in Antarctica: prototype development and results from the first operative phase
Bibliographic record
Abstract
In the beginning of the nineties the Italian National Antarctic Research Program has promoted a study aimed at the definition of an advanced automatic station able to operate with one year autonomy in Antarctic waters, allowing continuous collection of meteo-oceanographic data. The main results of the study were the demonstration of the feasibility of a concept based on a moored ice-resistent buoy able to allocate various instrumented modules, the definition of mission requirement and relevant sensing and electronic equipment, the identification of the most significant installation sites. In order to verify the concept in real operative conditions, a prototype of the station has been developed and installed in Antarctica during the 1993-94 Italian Expedition. The site chosen is located in Terra Nova Bay (Ross Sea) approximately 30 km south of the Italian Base, in about 450 meters water depth, and is characterized by the presence of a polynya. Once this first operative phase is completed, the station capabilities will be extended with the adoption of meteo-oceanographic sensors and other scientific packages. In the paper a description of the prototype station is given, and the results of the experimentation and data acquisition are presented and discussed.>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".