Roadmap Towards Communitywide Intercalibration and Standardization of Ocean Nucleic Acids ‘Omics Measurements
Bibliographic record
Abstract
In January 2020, the US Ocean Carbon & Biogeochemistry (OCB) Project Office funded the Ocean Nucleic Acids 'omics Intercalibration and Standardization workshop held at the University of North Carolina in Chapel Hill. Thirty-two participants from across the US, along with guests from Canada and France, met to develop a framework for standardization and intercalibration (S&I) of ocean nucleic acid ‘omics (na’omics) approaches (i.e., amplicon sequencing, metagenomics and metatranscriptomics). During the three-day workshop, participants discussed numerous topics, including: a) sample biomass collection and nucleic acid preservation for downstream analysis, b) extraction protocols for nucleic acids, c) addition of standard reference material to nucleic acid isolation protocols, d) isolation methods unique to RNA, e) sequence library construction, and f ) integration of bioinformatic considerations. This report provides a summary of these and other topics covered during the workshop and a series of recommendations for future S&I activities for na’omics approaches.
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.
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 | 0.164 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".