The Seaformatics technology demonstration project
Bibliographic record
Abstract
Memorial University of Newfoundland has completed a project entitled the Ocean Network Seafloor Instrumentation (later renamed Seaformatics Project), which began in 2007 and was funded by the Atlantic Canada Opportunities Agency (ACOA) - Atlantic Innovation Fund (AIF) and a number of other organizations. The concept behind Seaformatics was to develop technologies to enable the long-term deployment of an array of seafloor-mounted ocean sensors. The prototype node - called a Seaformatics Pod - has been successfully tested in Memorial University's Marine Institute flume tank and was field tested in Conception Bay in 2012. The project team proposed to perform a long term trial in Placentia Bay in partnership with Husky Energy. The project will provide much-needed data on the reliability of the Seaformatics Pod platform and prove that the Seaformatics Pod is capable of delivering ocean sensor data for other applications of interest to industry users. For Memorial University, success will result in a Seaformatics Pod prototype that is market-ready, which will in turn better enable the University to commercialize the technology for the global marketplace. This paper describes the 2nd generation pod prototype in detail, gives an overview of the demonstration projects goals and presents the preliminary results of the field program.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".