Diversity of the small subunit ribosomal RNA gene of the arbuscular mycorrhizal fungi colonizing Clintonia borealis from a mixed-wood boreal forest
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) communities in Clintonia borealis roots from a boreal mixed forests in northwestern Québec were investigated. Roots were sampled from 100 m2 plots whose overstory was dominated by either trembling aspen (Populus tremuloides Michx.), white birch (Betula papyrifera Marsh.), or mixed white spruce (Picea glauca (Moench) Voss) and balsam fir (Abies balsamea (L.) Mill.). Part of the 18S ribosomal gene of the AMF was amplified and the resulting PCR products were cloned. Restriction analysis of the 576 resulting clones yielded 92 different restriction patterns which were then sequenced. Fifty-two sequences closely matched other Glomus sequences from Genbank. Phylogenetic analysis revealed 10 different AMF sequence types, most of which clustered with other uncultured AM sequences from plant roots from various field sites. Compared with other AMF communities from comparable studies, richness and diversity were higher than observed in an arable field, but lower than seen in a tropical forest and a temperate wetland. The AMF communities from Clintonia roots under the different canopy types did not differ significantly and the dominant sequence type, which clustered with AM sequences from a variety of environments and hosts at distant geographical locations, represented 66.9% of all the clones analyzed.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".