GENETIC STRUCTURE VARIABILITY OF KELP <i>ALARIA MARGINATA</i> OVER SPACE AND TIME
Bibliographic record
Abstract
The genetic variability of Alaria marginata Postels & Ruprecht was investigated spatially and seasonally using the finger printing technique of amplified fragment length polymorphism (AFLP). Using 206 scoreable bands generated by one primer pair, individual plants that were separated by as little as a few decimeters to> 100 km could be distinguished, and followed an isolation‐by‐distance model. Genetic similarity ranged from 76% for patches (a few decimeters in diameter), to 71% for individual kelp stands (15 m across) and 67% for a group of stands separated by 185 km. Greater genetic similarity of patches occurred at the wave‐sheltered site than at wave‐exposed site. The influence of wave to genetic variability and the ability to predict gene flow on small stretch of beach were discussed. In one stand, genetic similarities were markedly different between seasons. This seasonal pattern may be the result of different age groups dominating the sampled stands over time. The genetic structure of A. marginata comprises local scale (patch and within stand) heterogeneity and larger scale (between stands) homogeneity.
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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 | 0.000 |
| 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 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".