EMSO — The European multidisciplinary seafloor and water-column observatory: Transition from planning to implementation
Bibliographic record
Abstract
EMSO (http://www.emso-eu.org) is a large-scale European Research Distributed Infrastructure (RI) of the ESFRI roadmap composed of fixed-point, seafloor and water-column observatories with the basic scientific objective of (near)-real-time, long-term monitoring of environmental processes across the geosphere, biosphere, and hydrosphere. It is geographically distributed in key sites of European waters, from the Arctic, through the Atlantic and Mediterranean, to the Black Sea. EMSO will be the sub-sea segment of the COPERNICUS (former GMES-Global Monitoring for Environment and Security) initiative and will significantly enhance the observational capabilities of European Member States. EMSO is the European counterpart of many similar worldwide infrastructures, such as ONC in Canada, OOI in US, DONET in Japan or IMOS in Australia. EMSO ended its Preparatory Phase, EU Framework 7 funded project in 2012, and now is in the Interim phase transitioning to the formation of the legal entity for managing the infrastructure: the EMSO European Research Infrastructure Consortium (hereinafter EMSO-ERIC). A phased implementation will characterize EMSO site extension, construction and operation. The overall duration of the first phase of EMSO implementation will be 5 years from the ERIC foundation, with a review point scheduled at year 3. From the technological point of view, the most striking characteristic of observatory design is its ability to address interdisciplinary objectives simultaneously across temporal and spatial scales. Data are collected from the surface ocean, through the water column, the benthos, and the sub-seafloor. Depending on the application, in situ infrastructures can either be attached to a cable, which provides power and enables data transfer, or operate as independent benthic and moored instruments. Data, in both cases, can be transmitted real-time through either fibre optic cables, or cable and acoustic networks that are connected to a satellite-linked buoys. Cabled infrastructures provide important benefits such as high power and bandwidth for realtime data transfer when a processing of huge amount of data (as for bioacoustics), or a real-time integration with land-based networks (as for the seismology), as well as rapid geo-hazard early warning systems. Test sites have shown technological challenges to be faced and the potential for answering important scientific questions.
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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 | 0.030 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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".