Early Marine Ecology of Juvenile Chinook Salmon on the Yukon Delta, Alaska, 2014-2015
Bibliographic record
Abstract
The data were collected in support of research primarily focused on assessing outmigration timing, diets, and energetic condition of juvenile Chinook salmon in the Yukon River and its estuary. This research was jointly funded by the Arctic-Yukon-Kuskokwim Sustainable Salmon Initiative (AYKSSI), which provided overall support for the entire research project, and the North Pacific Research Board (NPRB), which provided supplemental funding to support data collection of data in the offshore estuary of the Yukon River plume. The data were collected during research cruises in June, July and August of both 2014 and 2015. Data include biological and physical data from stations located on five transects set perpendicular to the Yukon Delta. Each transect has stations located at or near the 45ft, 35ft and 25ft depth contours. Data were submitted as a Microsoft Access database file (ACCDB). Tables from this database were extracted for archiving as CSV files by Axiom Data Science. This dataset includes the following files: NPRB_1308_Data_Catch.csv, NPRB_1308_Data_CTD.csv, NPRB_1308_Data_Event.csv, NPRB_1308_Data_Site.csv, NPRB_1308_Lookup_Family.csv, NPRB_1308_Lookup_SpeciesCodes.csv. This dataset was generated under NPRB project 1308.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".