Bibliographic record
Abstract
This is the OBIS extraction of the Ocean Tracking Network and University of British Columbia (UBC) Hinch Tags, 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=NEP.HNCH).Abstract:The Pacific Ocean Shelf Tracking (POST) project was designed to develop and promote the application of acoustic tagging technology to study the life history of Pacific salmon and other species migrating along the continental shelf of western North America. POST envisioned the eventual creation of a permanent continental-scale telemetry system, however, during its existence more limited pilot-scale arrays were deployed, primarily concentrated in the Pacific Northwest. These included several acoustic receiver curtains between Vancouver Island and the mainland, creating an excellent means by which to monitor coastal marine animal migrations, especially by juvenile salmonids (smolts) migrating to sea (see projects QCS, JDF and NSOG). In addition to arrays on the continental shelf, POST equipment was deployed upstream and in the estuaries of several major salmon-producing rivers. POST arrays, and POST data, were incorporated into the OTN in 2012. The integration of these arrays, their equipment and the associated animal tagging projects into OTN's global network allowed for international, widespread monitoring of important species within the Northeast Pacific Ocean. Tracking data generated from the POST arrays can be applied to the development of fishery management policies aimed at the sustainable harvest of resources, and to the understanding and conservation of other marine and diadromous species. Additional details about specific tracking projects which were originally a part of POST are only available by contacting the associated researcher.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.424 | 0.522 |
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".