Bibliographic record
Abstract
This is the OBIS extraction of the Ocean Tracking Network and Acadia University (Acadia U) Oakland Lake Eel, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=OAKEEL). Abstract:American eels (Anguilla rostrata) spawn in an unknown location in the Sargasso Sea. The larvae travel thousands of kilometres into fresh, estuarine, and marine waters along the western North Atlantic coastline. Seaward migration back to natal spawning grounds occurs in the fall. Eels play an important ecological role in aquatic communities, both as predator and prey, and are harvested in commercial, recreational, and aboriginal fisheries. Population declines have occurred in recent years, most notably in Ontario and Quebec, due to a combination of factors. In 2012, COSEWIC designated American eel as a threatened species, prompting the need for more information on their habitat use and abundance throughout their range. Since 2009, Oakland Lake, a protected water shed in Nova Scotia with restricted human access, has been an ideal study site for a long-term eel monitoring program. Using acoustic telemetry technology and lake bathymetry, seasonal and diel three-dimensional habitat use of eight American eels in Oakland Lake between July and October 2012 will be characterized.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".