Bibliographic record
Abstract
Seabed EM surveys in shallow water environments have a number of specific particularities. Specifically, there is difficulty with hermetical sealing of EM instruments and the necessity of overcoming electromagnetic noise caused by underwater currents and sea surface disturbances. Another problem is the inability to employ large ocean going vessels in many areas, while the use of small vessels increases the demands on the size and weight of the equipment. There are also certain positive aspects in this, pertaining to the ability to use reliable acoustic communication between the marine EM instrument positioned on the seabed and the sea surface, as well as the use of beacons for identifying the location of the bottom apparatus. In this paper, discussed is a shallow marine EM data acquisition equipment complex that allows efficient use of standard ground EM instruments for carrying out investigations at a sea depth interval of 0-200m. This complex consists of 2x - 4x - 5-channel marine EM systems.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".