A digital programmable high resolution 200 kHz water column profiler
Bibliographic record
Abstract
Acoustical instrumentation for imaging the water column has traditionally been ship mounted and configured to work in a downward looking orientation. Until recently, data acquisition for these acoustic instruments has used an analog strip chart recorder tended by an operator on board a surface vessel. With the advent of digital electronics, digital echo sounders have begun to appear. However, these instruments have followed the traditional configuration and, for the most part, have remained shipboard mounted. The past five years has seen unprecedented growth in the development of low power digital microprocessor, storage and data acquisition technologies. An acoustical 200 kHz high resolution, digital, programmable Water Column Profiler (WCP) has been developed incorporating these new technologies. The WCP offers unprecedented flexibility for the user and, except for the analog front end, is completely digital, fully programmable and is housed in a pressure case capable of bottom (upward looking), mooring or shipboard (downward looking) mounting configurations. The aluminum pressure case is capable of deployments to 200 m with connectors for telemetry and power if real time data are required. The WCP can ping at up to 2 Hz with an acoustic range resolution of 3 cm and is capable of digitizing four samples per acoustic range bin. The maximum probing depth, depending on the water column properties, is 200 m and the WCP is capable of storing data internally for up to 3 weeks at maximum ping and sampling rates. Data can be transferred realtime via a 10 Mbit/s 10Base2 Ethernet link to a surface system or local area network for viewing and/or data storage. The system can also be controlled remotely over the local area network. For self-contained autonomous in situ deployments, internally recorded data can be recovered from the WCP at very high rates to a storage system over a high speed Ethernet connection.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".