Bibliographic record
Abstract
Quentin Bone came from a family of well-known artists but, although he shared their talents, he chose to become a scientist because of his interest in natural history. After graduating in zoology from Oxford, he joined the scientific staff of the Marine Biological Association Laboratory at Plymouth, working there until retirement in 1991 and continuing thereafter as an emeritus research fellow. He was interested in all aspects of how fish swim, the structure and innervation of their swimming muscles, their metabolism, flotation and hydrodynamics. He showed that fishes have two distinct, independently innervated locomotory systems, red muscle for cruising and white muscle for rapid swimming bursts, and that the white muscle works on the basis of glycolytic metabolism, the red on oxidative. Later he showed that squids have convergently evolved two sorts of muscle fibre roughly equivalent to those of fishes. Bone took a comparative and evolutionary approach in all his work, looking for changes in design from simple to more complex systems and going right back to amphioxus, a putative ancestor of fishes. He also worked extensively on pelagic marine invertebrates that swim by jet propulsion—such as salps, doliolids and siphonophores—using optical and electron microscopy combined with electrophysiology to establish the neuromuscular basis of locomotion. In one such study he showed how salp chains, though lacking nervous connections between individual zooids, can swim in a coordinated manner using excitable epithelia. In another, using intracellular recordings and whole cell voltage clamp techniques, he was able to link changes in a siphonophore's swimming directly to changes in ion channel kinetics. While Bone's early studies on fish swimming established him as a leader in one important field, his later work on the behavioural physiology of a wide variety of pelagic marine invertebrates adds up to an equally outstanding body of work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.569 | 0.387 |
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".