Anadromous Waters Catalog (AWC) of Alaska, 2018
Bibliographic record
Abstract
This dataset contains the 2018 shapefiles of the Anadromous Waters Catalog, provided by the Alaska Department of Fish and Game (https://www.adfg.alaska.gov/sf/SARR/AWC/index.cfm?ADFG=maps.dataFiles). Water body numbers, locations, extent of cataloged habitat and species utilization of a given stream may change from year to year. Additionally, new water bodies are being added on an annual basis. It is the responsibility of the user to maintain an up to date version of the electronic data files. This data is not a legal document and should not be relied upon for making decisions regarding permitting needs. The user should contact the local office of the ADF&G to determine if a permit is required under AS 16.05.871 - 881 and 5 AAC 95.011. Also included is a figure showing the total stream kilometers per watershed for regions in Alaska. This figure was created using the AWC, in addition to two Canadian data sources (BC distributions: http://www.env.gov.bc.ca/esd/distdata/ecosystems/bc50kfiss/hist_fish_dist/; Yukon: http://cmnmaps.ca/fiss_yukon/) using ArcGIS.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.042 |
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".