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Record W4386201130 · doi:10.1093/gigascience/giad068

The founding charter of the Omic Biodiversity Observation Network (Omic BON)

2022· article· en· W4386201130 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGigaScience · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsAgriculture and Agri-Food Canada
FundersHorizon 2020 Framework ProgrammeNatural Environment Research CouncilEuropean CommissionBattelleNational Science Foundation
KeywordsOmicsCharterBiodiversityThematic mapData scienceGeographyBiologyComputer scienceEcologyBioinformaticsCartography

Abstract

fetched live from OpenAlex

Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge. Here, we present key elements of Omic BON's founding charter and first activities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0040.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.150
GPT teacher head0.321
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it