Species identification in deep water using multiple acoustic frequencies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multifrequency 12, 38, and 120 kHz acoustics were used to identify the dominant fish groups around a deepwater (>600 m) seamount (a known spawning site for orange roughy, Hoplostethus atlanticus) by amplitude mixing of the frequencies. This method showed three distinct acoustic groupings that corresponded to three groups of fishes based on size and swimbladder type: myctophids of total length less than 10 cm, morids and macrourids with lengths >30 cm, and orange roughy with a mean standard length of 36 cm. These three groups were the dominant groups caught in the demersal and pelagic trawls in the study area. A simple model of swimbladder resonance at depth of large and small gas-filled bladder fish groups is in agreement with our experimental observations. Traditionally, demersal and pelagic trawling is used to identify fish species in acoustic records. However, orange roughy are rarely caught in mid-water owing to net avoidance. Using three frequencies, these groups could be distinguished directly over their entire vertical extent from the acoustic records. This reduces a major source of positive bias uncertainty (factor range of 2.06.4) in the orange roughy biomass estimates.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it