Evaluation of MBari puck protocol for interoperable ocean observatories
Bibliographic record
Abstract
IEEE-1451[1] and OGC Sensor Web Enablement\n(OGC SWE)[2] define standard protocols to operate instruments,\nincluding methods to calibrate, configure, trigger data\nacquisition, and retrieve instrument data based on specified\ntemporal and geospatial criteria. These standards also provide\nstandard ways to describe instrument capabilities, properties, and\ndata structures produced by the instrument. These standard\noperational protocols and descriptions enable observing systems\nto manage very diverse instruments as well as to acquire, process,\nand interpret their data in a uniform and automated manner. We\nrefer to this property as “instrument interoperability”. This paper\ndescribes integration and evaluation of MBARI PUCK protocol\n[3] within different observatories including OBSEA [4,5] in\nSpain, the ESONET test-bed in Germany, and the SmartBay\nobservatory in Canada.
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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 | 0.031 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".