Assessment of DNA Barcoding for the Identification of Chenopodium murale L. (Chenopodiaceae)
Bibliographic record
Abstract
Chenopodium murale L. (Chenopodiaceae) is an erect annual herbaceous weed. This species is a threat for ecosystems worldwide as this annual-weed affects the growth and development of other plants by reducing the biological nitrogen-fixing ability. We evaluated the barcoding genes of the plastid region of C. murale [rbcL (Ribulose-1,5-bisphosphate carboxylase/oxygenase) and matK (Maturase K)] for the success of PCR amplification, the differential inter-specific divergences and the ability of a single gene or combination of rbcL and matK genes to discriminate C. murale as individual species. Online nucleotide database-search using individually produced sequences of rbcL and matK gene of the plastid region primarily identified the specimen as C. murale with 100% sequence similarity. The single gene matK showed better resolution of the tree compared with the other phylogenetic-trees that were inferred from the single rbcL gene sequence or the combination of sequences of rbcL and matK. We found that single gene sequence of matK had high discrimination efficiency for the identification of the species C. murale as well as for the other 11 species (C. album, C. ambrosioides, C. bonus-henricus, C. ficifolium, C. foliosum, C. glaucum, C. polyspermum, C. rubrum, C. simplex, C. urbicum & C. vulvaria) under the genus Chenopodium.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".