A Nonlethal, Rapid Method for Assessing the Somatic Energy Content of Migrating Adult Pacific Salmon
Bibliographic record
Abstract
Abstract Traditional methods for determining the energy content of fish involve either chemical assays of lipid and protein levels (proximate analyses) or tissue combustion (bomb calorimetry). In studies of migrating Pacific salmon Oncorhynchus spp., entire fish need to be homogenized prior to analysis, as energy reserves are stored along a head‐to‐tail gradient and change along this gradient depending on the stage of upriver migration. The logistics and costs associated with transporting carcasses to the laboratory can be prohibitive. Also, many populations of Pacific salmon are at risk of extinction, so lethal sampling is often not an option. Few reliable and practical methods exist that enable rapid and nonlethal energy determinations of large fish in the field. We evaluated a handheld microwave energy meter as a means of estimating whole‐body energy concentrations. In 2002 and 2003, we collected sockeye salmon O. nerka from several stocks during their coastal and upriver migration through the Fraser River watershed (British Columbia). For each stock, we sampled fish from various locales ranging from ocean to spawning areas. Fish somatic tissues were interrogated at four body positions; however, the two most anterior positions produced the most accurate energy information. It took less than 30 s per fish to collect these data. We found strong regression relationships between somatic lipid percentage (R2 = 0.93; P < 0.001) and gross somatic energy density (R2 = 0.94; P < 0.001) measured by whole‐carcass proximate analyses and loge transformed energy meter readings. The slopes and intercepts of these relationships did not differ among stocks or years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".