Real-time PCR quantification of <i>Colletotrichum coccodes</i> DNA in soils from bioherbicide field-release assays, with normalization for PCR inhibition
Bibliographic record
Abstract
A real-time polymerase chain reaction (PCR) assay was developed to quantify simultaneously the biocontrol agent Colletotrichum coccodes (DAOM 183088) and soil compounds inhibitory to PCR. The external control used in this assay was spiked at known concentrations in soil DNA extracts and amplified in real-time PCR with its own primer set. A comparison between the estimated quantities of the external control and the known quantities added to the extracts allowed an estimation of the PCR efficiency on a sample per sample basis in 18 extracts of soil DNA analyzed, originating from the bioherbicide field-release trials. All 18 extracts tested positive for the presence of inhibitory compounds, but with substantial variability in the magnitude of PCR efficiency (from 12% to 82%) from 1 g of soil sample to another, even when soil DNA extracts had been diluted. This variability demonstrates quantitatively the heterogeneity of soil with regards to content in PCR-inhibitory compounds. The differences in amplification efficiency were used to normalize the amounts of target C. coccodes DNA previously quantified from the same samples.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".