The Global Omics Observatory Network: Shaping standards for long-term molecular observation
Bibliographic record
Abstract
Founded in early 2018 through a collaboration between the EU Horizon 2020 AtlantOS project and Agriculture and Agri-Food Canada, the Global Omics Observatory Network (GLOMICON) is federating long-term ecological observatories employing "omic" (e.g. metagenomcis, metatranscriptomics, metabolomics) techniques to assess biodiversity across scales. GLOMICON is the consolidation of a series of meetings and ad hoc efforts (e.g. the multi-omic sessions at TDWG 2017) and seeks to mainstream multi-omic observation in existing observatory systems. GLOMICON currently networks >40 organisations observing biodiversity from urban and agricultural systems to the depths of the polar ocean. Coordination through GLOMICON allows the long-term observatory community to develop and align their needs, thus approaching standards bodies including the Genomic Standards Consortium (GSC), the Biodiversity Information Standards (TDWG) organisation, and the Earth Science Information Partners (ESIP) with a common voice. Further, as more ecological observatories begin to adopt molecular techniques, GLOMICON offers a community building best practices to facilitate their operationalisation. Vitally, GLOMICON interfaces with established observation networks via organisations such as UNESCO/IOC Global Ocean Observing System through its Biology and Ecosystems Panel. Such interactions have provided invaluable guidance on how to approach global standardisation in a firmly operational and multi-stakeholder environment, while ensuring innovative science can thrive. In this contribution, we will deliver a briefing on GLOMICON's current priorities and efforts to shape molecular standards to become fit-for-purpose in observatory-grade settings. In particular, we will focus on our interactions with other key omic observing networks, including the Genomic Observatories Network, and our joint strategies to progress towards an distributed yet integrated system. We will also note practical steps the network has taken to systematise protocols and best practices, (bio)informatics routines, observatory parameters, and global intercalibration through sample exchange. Lastly, we will note the network's upcoming priorities, which feature the need to develop strategies for sustainability and the extension of coordination efforts between national, regional, and global Earth observation 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 | 0.190 | 0.120 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".