Acoustic seabed classification of demersal capelin spawning habitat in coastal northeast Newfoundland
Bibliographic record
Abstract
In this study, acoustic remote sensing tools and techniques were used to map, classify and characterize demersal (off beach) capelin (Mallotus villosus, Mülller, 1776) spawning. -- Historically, capelin are known to spawn on and near modem gravel beaches in coastal Newfoundland and demersally on the Southeast Shoal on the Grand Banks. Recently, capelin were observed spawning demersally at seven sites on the northeast coast of Newfoundland. These demersal sites were compared to previously studied beach sites around Newfoundland. Sea water temperature was determined to be the primary factor controlling the occurrence of capelin spawning. Spawning can occur on beaches or demersally when sea water temperatures are between 2°C and 12°C. Depth and temperature are highly correlated such that the depth of the capelin spawning sites was dependent on the depth of the 2°C to 12°C isotherms. -- The second factor that controls capelin spawning is seafloor sediment. Beach and demersal spawning occurred on poorly-sorted postglacial sand and gravel sediments at water depths of 18 m to 33 m. The postglacial sediments from these sites are linked to changes in sea-level and may have been deposited around 8600 (radiocarbon) years ago when the postglacial lowstand of the sea-level of the study area was situated 17-18 m below present sea-level. -- Supervised acoustic classification identified four different seabed types: fine sand, gravel (a mixture of medium sand to coarse pebble), cobble-boulder-bedrock, and macroalgae. Capelin spawning at most sites occurred on gravel, but at two sites spawning was associated with fine sand. The supervised acoustic classification of the seabed was achieved by matching acoustic signatures to ground-truth data from grab samples and images captured with a remotely operated vehicle (ROV) equipped with a video camera.
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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 | 0.000 | 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".