Trilobite ‘pelotons’: possible hydrodynamic drag effects between leading and following trilobites in trilobite queues
Bibliographic record
Abstract
Abstract Energy saving mechanisms in nature allow following organisms to expend less energy than leaders. Queues, or ordered rows of individuals, may form when organisms exploit the available energy saving mechanism while travelling at near‐maximal sustainable metabolic capacities; compact clusters form when group members travel well below maximal sustainable metabolic capacities. The group size range, given here as the ratio of the difference between the size of the largest and smallest group members, and the size of the largest member (as a percentage), has been hypothesized to correspond proportionately to the energy saving quantity because weaker, smaller, individuals sustain the speeds of stronger, larger, individuals by exploiting the energy saving mechanism (as a percentage). During migration, small individuals outside this range may perish, or form sub‐groups, or simply not participate in migratory behaviour. We approximate drag forces for leading and following individuals in queues of the late Devonian ( c . 370 Ma) trilobite Trimerocephalus chopini . Applying data from literature on Rectisura herculea , a living crustacean, we approximate the hypothetical walking speed and maximal sustainable speeds for T. chopini . Our findings reasonably support the hypothesis that among the population of fossilized queues of T. chopini reported in the literature, trilobite size range was 75%, while the size range within queues was 63%; this corresponds reasonably with drag reductions in following positions that permit c . 61.5% energy saving for trilobites following others in optimal low‐drag positions. We model collective trilobite behaviour associated with hydrodynamic drafting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".