Pacific Region Commercial Salmon Fishery In-season Catch Estimates
Bibliographic record
Abstract
The Fishery Operations System (FOS) is the Department of Fisheries and Oceans Canada’s (DFO) centralized Oracle database that holds commercial salmon fishery catch, effort and biological data. The FOS database was built in 2001 and continues to be the current repository for all data pertaining to DFO’s Pacific Region Commercial Salmon Logbook program.The Commercial Salmon Logbook program was initiated in 1998 with fleet wide participation made mandatory during the 2001 season. The program requires all commercial salmon fishers to record their daily catch and effort information in a harvest logbook and to subsequently report it to DFO using a service provider within deadlines defined in the conditions of licence. A portion of the information collected from the logbook program contains fisher personal information and is therefore protected and un-releasable. Fishery Managers use the fisher reported catch and effort, in addition to information collected from other sources such as overflights, to calculate in-season catch estimates. NOTES: This report contains ONLY commercial catch estimates — it DOES NOT include testfishing, recreational or First Nations data. These figures are preliminary in-season catch estimates and are subject to change. Consult the applicable Fishery Manager or Biologist as to the status of particular catch estimates. All catch estimates are reported in pieces (numbers of fish). Catch estimates include adults and jacks combined ("jacks" are small but sexually mature early-return males).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".