Demography of genets of clonal red seaweeds: current limitations and proposed solutions using genetic markers from experimental populations
Bibliographic record
Abstract
For clonal red seaweeds, the genet is defined as the thallus that develops from a single spore. The demography of genets for these organisms is poorly known. This results from the inability of visually detecting genets when ramets (fronds) are abundant, when separate thalli actually represent fragments of one original genet, and when holdfast coalescence occurs between neighboring genets. The use of genetic markers, such as allozymes and certain DNA regions, has allowed for the identification of genets in natural populations of clonal terrestrial plants. However, this may not work for natural populations of clonal red seaweeds, because several genets may be produced by asexual spores from the same individual, rendering those genets unidentifiable with certain genetic mrkers. A useful approach could be to study experimental populations under controlled laboratory conditions. The position and shape of genets could be monitored as they develop from genetically distinct spores, selected as such on purpose. Once the visual identification of genets becomes impossible due to the increasing density of ramets, mapping the different ramet genotypes shoul aloow for the continuous identification of genets. Some genetic variation could arise within genets through somatic mutation and genetic transportation. Rates of these processes are largely unknown for clonal seaweeds, so they should be first estimated to determine their potential effects on demographic studies based on genetic 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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".