Bibliographic record
Abstract
Sparked by anecdotal accounts of boat noise influencing the catch rates of commercial salmon trollers on the B.C. coast, acoustical studies of both boats and fish were undertaken. The study was in four parts: 1. Acoustical output of salmon trollers: Recordings were made of troll vessels and examined on a spectrum analyzer. Sonic output was predominantly of low frequency, under 300 Hz. Output levels at trolling speed (1-2 m/s) were about 20 dB re 1 μbar at 1 meter from the hull. Higher frequency spikes (1-2.5 kHz) were observed with operation of hydraulic pumps for auxiliary equipment. Broadband, transient output (approximately 1-6 kHz), was thought to be correlated with cavitation from propellors. 2. Fish sounds: Recordings were made of herring, salmon and rainbow trout swimming rapidly and feeding on pellets in net pen enclosures. These were examined on a spectrum analyzer. Two types of sounds were evident, "knocks" and "scratches". Knocks were correlated with rapid swimming and maneuvering and are likely of hydrodynamic origin. Scratches were thought to be produced by branchiate and skeletal movements and were relatively faint. Knocks were l-2 kHz, scratches 3.5-5.5 kHz. The dominant sounds in actively feeding, subsurface salmonids, were knocks. Recordings of feeding schools sounded remarkably like trickling water to the human ear. 3. Attracting salmon in net pens: Attempts were made to lure coho (Oncorhynchus kisutch) and chinook (Oncorhynchus tschawy tscha) as well as rainbov/ trout (Salmo gairdneri) to a speaker projecting recorded feeding sounds of the target fish. No responses of any kind were observed to output levels as high as 55 dB re 1 μbar at 1 meter. 4. Attracting salmon at sea: Recorded and simulated feeding and swimming sounds of salmonids were projected within the gear array of a commercial salmon troller fishing on the west coast of Vancouver Island, B.C. Catch rates were monitored with the test sounds on and off. Output level was 55 dB re 1 μbar at 1 meter. No significant change in catch rate was observed in response to the test sounds.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".