Something from (almost) nothing: the impact of multiple displacement amplification on microbial ecology
Bibliographic record
Abstract
Microbial ecology is a field that applies molecular techniques to analyze genes and communities associated with a plethora of unique environments on this planet. In the past, low biomass and the predominance of a few abundant community members have impeded the application of techniques such as PCR, microarray analysis and metagenomics to complex microbial populations. In the absence of suitable cultivation methods, it was not possible to obtain DNA samples from individual microorganisms. Recently, a method called multiple displacement amplification (MDA) has been used to circumvent these limitations by amplifying DNA from microbial communities in low-biomass environments, individual cells from uncultivated microbial species and active organisms obtained through stable isotope probing incubations. This review describes the development and applications of MDA, discusses its strengths and limitations and highlights the impact of MDA on the field of microbial ecology. Whole genome amplification via MDA has increased access to the genomic DNA of uncultivated microorganisms and low-biomass environments and represents a 'power tool' in the molecular toolbox of microbial ecologists.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".