It Pays to Be Bumpy: Drag Reducing Armor in the Pacific Spiny Lumpsucker, <i>Eumicrotremus orbis</i>
Bibliographic record
Abstract
Armor is a multipurpose set of structures that has evolved independently at least 30 times in fishes. In addition to providing protection, armor can manipulate flow, increase camouflage, and be sexually dimorphic. There are potential tradeoffs in armor function: increased impact resistance may come at the cost of maneuvering ability; and ornate armor may offer visual or protective advantages, but could incur excess drag. Pacific spiny lumpsuckers (Eumicrotremus orbis) are covered in rows of odontic, cone-shaped armor whorls, protecting the fish from wave driven impacts and the threat of predation. We are interested in measuring the effects of lumpsucker armor on the hydrodynamic forces on the fish. Bigger lumpsuckers have larger and more complex armor, which may incur a greater hydrodynamic cost. In addition to their protective armor, lumpsuckers have evolved a ventral adhesive disc, allowing them to remain stationary in their environment. We hypothesize a tradeoff between the armor and adhesion: little fish prioritize suction, while big fish prioritize protection. Using micro-CT, we compared armor volume to disc area over lumpsucker development and built 3D models to measure changes in drag over ontogeny. We found that drag and drag coefficients decrease with greater armor coverage and vary consistently with orientation. Adhesive disc area is isometric but safety factor increases with size, allowing larger fish to remain attached in higher flows than smaller fish.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".