Ocean Networks Canada: From Geohazards Research Laboratories to Smart Ocean Systems
Bibliographic record
Abstract
Ocean Networks Canada (ONC; http://www.oceannetworks.ca) operates the NEPTUNE and VENUS cabled ocean observatories off the western coast of Canada (Figure 1) and an increasing number of miniature ocean observatories, such as in the Canadian Arctic. These observatories collect data on physical, chemical, biological, and geological properties of the ocean and seafloor over long time periods, supporting research on complex Earth processes in ways not previously possible (Taylor, 2009; Barnes et al., 2012, 2013). All recorded data are permanently archived and publicly available in real time through ONC's Oceans 2.0 data portal. Much of the data collected by ONC is related to marine geohazards, such as earthquakes, tsunamis, submarine landslides, waves, and gas hydrate stability. These real-time data are used by early warning centers and could be made available to decision makers through Smart Ocean Systems (http://www.oceannetworks.ca/technology-services/smart-ocean-systems).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.020 |
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".