Comparison of bacterial 16S rRNA variable regions for microbiome
Bibliographic record
Abstract
Agradecimentos: This project was supported by NSERC Discovery grants to F. Sperling (RES0016259) and K. Magor (228035-2010 and RGPIN 2015-05045), J. Sperling is supported by an Alberta Innovates Technology Futures Graduate Student Scholarship, K. Silva-Brandão was supported by the Brazilian Science Without Borders program fellowship (CNPq PDE/CSF 200942/2012-3) and M. Brandão was supported by FAPESP GRANT 2011/00417-3. We thank LifeTech (DNA extraction kits), Ion Torrent (Library Quantification, Metagenomics kit, Barcodes) for generous in-kind gifts. Ted Barney of Long Point Waterfowl, Beck Vet Clinic, Animal Care Hospital of Williams Lake and Andrew Derocher provided tick specimens. We also gratefully acknowledge the comments of two anonymous reviewers
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".