Corrigendum: Diversity of reductive dehalogenase genes from environmental samples and enrichment cultures identified with degenerate primer PCR screens
Bibliographic record
Abstract
A corrigendum onDiversity of reductive dehalogenase genes from environmental samples and enrichment cultures identified with degenerate primer PCR screens.by Laura A. Hug and Elizabeth A. Edwards (2013). Front. Microbiol. 4:341 doi: 10.3389/fmicb.2013.00341The PCR amplification conditions were inaccurate as originally published, omitting the number of cycles for the final amplification step – a total of 25 cycles should be conducted when annealing at 50°C. The corrected methods are included below.The following conditions were subsequently applied to all described samples: an initial denaturation at 95°C for 5 min, three cycles of denaturation at 95°C for 30 s, primer annealing at 38°C for 30 s, and elongation at 72°C for 90 s, three cycles of amplification denaturation at 95°C for 30 s, primer annealing at 45°C for 30 s, and elongation at 72°C for 90 s, and 25 cycles of denaturation at 95°C for 30 s, primer annealing at 50°C for 30 s, and elongation at 72°C for 90 s, and a final extension at 72°C for 10 min.Conflict of Interest StatementThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.093 | 0.061 |
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".