Bibliographic record
Abstract
geographic distribution of many fish and shellfish stocks vary in response to environmental change. Therefore, to help understand the cause of observed fluctuations in fish and shellfish resources and eventually predict future changes, we seek to describe and understand the ocean climate and its variability. Catches of most major fish and shellfish species off eastern Canada have centered on offshore banks but most of the continental shelf, including estuaries and embayments, from Hudson Strait to the Gulf of Maine are commercially exploited. In addition, the habitat of anadromous (e.g. salmon) and catadramous species (e.g. eels) extend from the inland river systems to the deep open ocean at different times of the year. Climate summaries of the physical oceanographic conditions (mainly water temperature and salinity) within this broad geographic area are gathered from standard monitoring stations, regional resource surveys, process-oriented research studies, ships-of-opportunity, fishing vessels. and satellite imagery. Additional data on hydrological, meteorological and sea ice conditions are collected or gathered from various government departments. All of the hydrographic data are edited and archived in Canada's national Marine Environmental Data Service (MEDS) data base. A working copy is maintained in a zonal data base at the Bedford Institute of
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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.136 | 0.043 |
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".