AFLP characterization of three argentine <i>Coprotus</i> species
Bibliographic record
Abstract
AFLP methodology was applied to characterize three Coprotus species (C. lacteus, C. niveus, C. sexdecimsporus) so as to estimate the levels of polymorphism within species, to analyze the phenetic relationships among them, and to contrast the AFLP findings to those of a previous RAPD study. The high number of AFLP bands obtained with the six assayed primers allowed us to detect intra-specific variability. The genetic variability within species obtained using AFLP (measured in terms of percentage of polymorphic loci) was two to three times higher than those obtained by RAPD. The phenograms generated by AFLP markers grouped all strains of the same species into three defined clusters, and a higher association between C. lacteus and C. sexdecimsporus was also observed. The AFLP technique could become a powerful tool for genera such as Coprotus, in which a high intra-specific homogeneity does not allow detection of genetic variability using other PCR-based markers.
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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 | 0.000 |
| 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".