Molecular analyses of protists in long-term observation programmes—current status and future perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Protists (microbial eukaryotes) are diverse, major components of marine ecosystems, and are fundamental to ecosystem services. In the last 10 years, molecular studies have highlighted substantial novel diversity in marine systems including sequences with no taxonomic context. At the same time, many known protists remain without a DNA identity. Since the majority of pelagic protists are too small to identify by light microscopy, most are neither comprehensively or regularly taken into account, particularly in Long-term Ecological Research Sites. This potentially undermines the quality of research and the accuracy of predictions about biological species shifts in a changing environment. The ICES Working Group for Phytoplankton and Microbial Ecology conducted a questionnaire survey in 2013–2014 on methods and identification of protists using molecular methods plus a literature review of protist molecular diversity studies. The results revealed an increased use of high-throughput sequencing methods and a recognition that sequence data enhance the overall datasets on protist species composition. However, we found only a few long-term molecular studies and noticed a lack of integration between microscopic and molecular methods. Here, we discuss and put forward recommendations to improve and make molecular methods more accessible to Long-term Ecological Research Site investigators.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it