Herring spawning areas of British Columbia: A review, geographic analysis and classification
Bibliographic record
Abstract
The geographical distributions of Pacific herring (Clupea pallasi) spawning sites have been estimated each year since 1928. The analysis was based on approximately 29,000 spawning events recorded mostly by fishery officers and diver teams in six regions of the British Columbia (BC) coast. For each of about 100 geographical sections of BC, time series bubble plot maps were constructed to delineate annual herring spawn deposition along each kilometre of shoreline from 1930 to the year 2001. Cumulative spawn deposition (from 1928 to 2006) was also mapped using proportionately sized, multicoloured, bubble plots which rank and classify each kilometre of herring spawning habitat according to the long-term frequency and magnitude of spawns over time. The analysis was conducted coast-wide, so that any kilometre on the BC coast could be compared with any other kilometre. Approximately 5,260 km (or 18 %) of British Columbia's extensive 29,500 km coastline have been ranked and classified as herring spawning habitat. An estimated 450 to 600 kilometres (or about 1.8 % of BC shoreline) is utilized by spawners in a typical year. The approximate shapes of herring spawn depositions were also digitized over a 1:20,000 scale, Terrain Resource Information Management (TRIM) map for the years 1930 to 2002. Composite spawn maps for each section of BC were created by chronologically overlaying spawn polygons. In 2005, Arcview©
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".