Foraging mechanisms in excavate flagellates shed light on the functional ecology of early eukaryotes
Bibliographic record
Abstract
The phagotrophic flagellates described as "typical excavates" have been hypothesized to be morphologically similar to the Last Eukaryotic Common Ancestor and understanding the functional ecology of excavates may therefore help shed light on the ecology of these early eukaryotes. Typical excavates are characterized by a posterior flagellum equipped with a vane that beats in a ventral groove. Here, we combined flow visualization and observations of prey capture in representatives of the three clades of excavates with computational fluid dynamic modeling, to understand the functional significance of this cell architecture. We record substantial differences amongst species in the orientation of the vane and the beat plane of the posterior flagellum. Clearance rate magnitudes estimated from flow visualization and modeling are both like that of other similarly sized flagellates. The interaction between a vaned flagellum beating in a confinement is modeled to produce a very efficient feeding current at low energy costs, irrespective of the beat plane and vane orientation and of all other morphological variations. Given this predicted uniformity of function, we suggest that the foraging systems of typical excavates studied here may be good proxies to understand those potentially used by our distant ancestors more than 1 billion years ago.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".