Caudal differential pressure as a predictor of swimming speed of cod (<i>Gadus morhua</i>)
Bibliographic record
Abstract
We report the results of an experiment designed to investigate the feasibility of using differential pressure to estimate the swimming speed and metabolic rate of Atlantic cod (Gadus morhua). Seven cod were fitted with a miniature differential pressure sensor mounted on one side of the caudal peduncle immediately anterior to the base of the caudal fin rays. Relationships between differential pressure, tailbeat frequency, tailbeat amplitude, swimming speed and rate of oxygen consumption ((O(2))) were determined as a function of the swimming speed of cod swimming at 5 degrees C in a recirculating 'Brett-style' respirometer. Tailbeat differential pressure, tailbeat amplitude and tailbeat frequency were highly correlated with swimming speed. The average or integrated pressure ranged from 0 to 150 Pa for speeds up to 0.8 m s(-1) (1.1 L s(-1), where L is total body length), while the 'pressure difference' (maximum minus minimum pressure) ranged from 0 to 900 Pa. Small changes in swimming speed of less than 0.05 m s(-1) were readily detected as differences in tailbeat pressure. Burst swimming in the respirometer resulted in huge pressure 'bursts' of up to 5000 Pa 'pressure difference'. The rate of oxygen consumption increased exponentially and was highly correlated with swimming speed (r(2)=0.77). The rate of oxygen consumption was also correlated with tailbeat integrated pressure (r(2)=0.68) and with differential pressure (r(2)=0.43); regression correlations were always greater for individuals than for combined data from all cod. The results detailed in this study indicate that an ultrasonic differential pressure transmitter would enable accurate estimates of the swimming speed, rates of oxygen consumption and activity patterns of free-ranging fish in nature.
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) | 0.000 | 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) | 0.000 | 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".