The Impact of Age and Catch Location on the Mortality Rates of Striped Bass
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Striped bass are one of the most popular and sought-after gamefish in the United States for recreation and commercial fishermen. This popularity comes from their size, with many fish reaching 40+ pounds, a prominent dish in seafood restaurants, and their expansive habitat as they inhabit waters from Florida to Canada (1). During the late 1970s/80s, the population began sharply declining due to overfishing, and governments enacted regulations to stabilize the population (1). However, as of 2020, overfishing is still occurring, and regulations are continuously evolving (1). Each state has their own rules and regulations for possessing striped bass for commercial and recreational fishermen. This study examines how the age and catch location of the fish influences the mortality rates. This study aims to see if specific age ranges or areas have higher mortality rates and if state governments could place regulations to protect these fish in these vulnerable regions.BIO 340 final project
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it