Review of recent research on Southern Resident Killer Whales to detect evidence of poor body condition in the population
Bibliographic record
Abstract
This review was commissioned by the SeaDoc Society in light of major concern for the population trajectory of the SRKW population. The review focuses on identifying evidence for poor body condition in the SRKW population from information presented in Seattle, March 6 2017 (see Appendix 1 Agenda). Body condition can be influenced by food availability (quantity and quality), energy balance, disease, toxin exposure, physiological status, genetics and stress from noise and vessel traffic, amongst other factors, although food availability is the most common cause in wild mammalian populations. For SRKW, food availability to individuals is determined by both prey availability and time to find, catch, share and consume prey. Anthropogenic disturbance will reduce food consumption and thus influence body condition. The small population size and complex social structure of SRKW complicate detection of associations between measures of body condition and population dynamics. Stochastic events can skew population-wide trends substantially. Therefore, individual cases must be considered rather than analyses of trends and correlations on limited-sample-sizes. The small sample size problem hinders many analyses of this population's ecology. A recent shift in distribution of Northern Resident Killer Whales (NRKW) into offshore SRKW range complicates choice of a control population. NRKW could compete for space and prey, and may be influenced by environmental variables that influence SRKW. Thus when using a case control approach, and comparing parameters between SRKW and a reference population, care should be taken when using the NRKW, and another population should be used such as the southern Alaskan residents.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".