Oceanic distribution and behavior of green sturgeon
Bibliographic record
Abstract
Pop-off archival tags (PATs) and trawl logbook data were used to study the distribution, movement, and behavior of green sturgeon Acipenser medirostris off the U.S. and Canadian west coasts.Seven green sturgeon were tagged with PATs in the Rogue River, Oregon, during the autumn months of 2001 and 2002.All fish left the Rogue River and entered the ocean within 32 d of tagging.Six of seven tags popped off and transmitted data to satellites, as planned, 2.5 to 7.7 months after the fish left the Rogue River.One tag detached prematurely 5.7 months after tagging, but it drifted ashore in northern Oregon and was returned.All PAT-tagged sturgeon migrated north of the Rogue River after entering the ocean; pop-off locations ranged from the central Oregon coast to northwestern Vancouver Island, Canada.Estimated distances migrated through nearshore waters ranged from 221 to 968 km.Potential concentration sites off the Oregon and Washington coasts were identified using PAT and Oregon trawl logbook data sets.Green sturgeon exhibited a narrow and shallow depth distribution (typically < 100 m) over the continental shelf.This limited depth distribution makes green sturgeon vulnerable to trawl bycatch in the open ocean, which will increase if trawling within the narrow depth range increases.Although green sturgeon with PATs typically occupied depths of 40-70 m, they also occasionally made what appeared to be rapid vertical ascents to or near the surface.Green sturgeon tagged with PATs often were more active and occupied shallower depths at night than during the day.Green sturgeon are harvested by commercial, treaty, and sport fisheries.Because the population trends and abundance of green sturgeon are uncertain, and because green sturgeon from the main spawning rivers are probably mixed along the U.S. West Coast, conservative management measures should be implemented throughout the species' range to limit fishing mortality and ensure effective conservation.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".