Estimation of Stock Composition and Individual Identification of Sockeye Salmon on a Pacific Rim Basis Using Microsatellite and Major Histocompatibility Complex Variation
Bibliographic record
Abstract
Abstract The variation at 14 microsatellite loci and one major histocompatibility complex (MHC) locus was surveyed for over 48,000 sockeye salmon Oncorhynchus nerka sampled from 299 localities ranging from the Columbia River to Japan. For the microsatellite loci, the number of alleles observed at a locus was related to the power of the locus in providing accurate estimates of stock composition of single‐population mixtures. In an analysis of single‐population mixtures where the Pacific Rim baseline was used for estimation of stock identification, 80% accuracy for the average population was achieved by employing approximately 80 alleles in the analysis. Increasing the accuracy of estimated stock compositions to 90% for the average population required approximately 400 microsatellite alleles. When all loci were used to estimate stock compositions, estimates were above 80% for all sampling sites or populations, above 90% for the lake of origin, and generally above 95% for the region of origin. Analysis of known‐origin samples indicated that accurate lake or regional estimates of stock composition were obtained. The accuracy of identification of individual fish to the correct lake of origin was above 90%, regardless of whether the lakes were geographically widespread or within a single watershed. The estimated stock compositions of mixed‐fishery samples from the western Bering Sea, from the continental shelf near Kodiak Island in the Gulf of Alaska, from Southeast Alaska, and from Johnstone Strait in southern British Columbia were markedly different among samples. These stock compositions reflected geographical variation in fishery locations and variation in the migration pathways of either juvenile or maturing sockeye salmon. Variation of DNA enabled us to estimate accurately the origin of individual fish and the composition of mixed‐stock samples from any location in the Pacific Rim distribution of sockeye salmon.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".