A molecular identification protocol for roots of boreal forest tree species
Why this work is in the frame
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Bibliographic record
Abstract
PREMISE OF THE STUDY: Roots play a key role in many ecological processes, yet our ability to identify species from bulk root samples is limited. Molecular tools may be used to identify species from root samples, but they have not yet been developed for most systems. Here we present a PCR-based method previously used to identify roots of grassland species, modified for use in boreal forests. • METHODS: We used repeatable interspecific size differences in fluorescent amplified fragment length polymorphisms of three noncoding chloroplast DNA regions to identify seven woody species common to boreal forests in Alberta, Canada. • RESULTS: Abies balsamea, Alnus crispa, Betula papyrifera, Pinus contorta, and Populus tremuloides were identifiable to species, while Picea glauca and Picea mariana were identifiable to genus. In mixtures of known composition of foliar DNA, species were identified with 98% accuracy using one region. Mixed root samples of unknown composition were identified with 100% accuracy; four species were identified using one region, while three species were identified using two regions. • DISCUSSION: This methodology is accurate, efficient, and inexpensive, and thus a valuable approach for ecological studies of roots. Furthermore, this method has now been validated for both grassland and boreal forest systems, and thus may also have applications in any plant community.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it