High-frequency diatom dynamics seen in an ice- and snow-covered temperate lake using an imaging-in-flow cytometer
Bibliographic record
Abstract
Abstract The study of winter in temperate, ice-covered lakes has largely been neglected, creating a major gap in our understanding of annual phytoplankton cycles. We assessed patterns in biovolumes of Asterionella, cf. Synedra, Urosolenia, and total phytoplankton at three depths during the winter of 2014/2015 as estimated using images from an Imaging FlowCytobot (IFCB) moored in Lac (Lake) Montjoie, Quebec (Canada). Even though the use of the IFCB under-ice presented challenges, these were outstripped by its advantages. The IFCB provided unprecedented high temporal and spatial resolution phytoplankton count and biovolume data that allowed patterns of abundance to be observed in detail. Interestingly, the IFCB captured an abundance of Urosolenia , which may be dissolved in standard Lugol’s-preserved grab samples. We found Asterionella grew until mid-December and then slowly decreased towards the spring, whereas cf. Synedra diatoms decreased from early December and then rebounded towards late December as light increased before falling again towards the spring. Urosolenia peaked in late December as cf. Synedra diatoms rebounded and then began to decline towards the spring. Total phytoplankton declined towards late December, increased in the beginning of January and then declined towards the spring. The studied diatoms maintained considerable under-ice seed populations and grew when light was sufficient.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".