COMPARISON OF THREE COMMON MOLECULAR TOOLS FOR DISTINGUISHING AMONG GEOGRAPHICALLY SEPARATED CLONES OF THE DIATOM <i>SKELETONEMA MARINOI</i> SARNO ET ZINGONE (BACILLARIOPHYCEAE)<sup>1</sup>
Bibliographic record
Abstract
Skeletonema marinoi Sarno et Zingone is a planktonic marine diatom with a widespread geographic distribution. Different populations of this species may show distinct genetic signatures. We have evaluated the utility of three common molecular methods for distinguishing clones of S. marinoi from different geographic regions. Clonal cultures were isolated from the Canadian west coast, south west Portugal, and the east and west coasts of Sweden. All strains originated from resting stages in sediment. More than 90% of the individually isolated chains grew to densities suitable for DNA extraction. Genetic signatures of clones from each sample location were assessed by sequencing variable domains (D1–D3) of the nuclear large subunit (LSU) rRNA gene and internal transcriber spacer (ITS) (ITS‐1, 5.8S and ITS‐2) regions, and also by analysis of randomly amplified polymorphic DNA patterns. Analysis of molecular variance showed that strains from the four geographic areas were significantly separated by all three methods but that differences among European samples were best resolved by ITS 2 sequences.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".