Bomb radiocarbon age validation of Pacific ocean perch (Sebastes alutus) using new statistical methods
Bibliographic record
Abstract
We used bomb-produced radiocarbon (14C) to validate ages of Pacific ocean perch ( Sebastes alutus ), which are routinely estimated with the cut-and-burn method at the Alaska Fisheries Science Center (Seattle, Washington, USA). New statistical methods to compare Δ14C in validation samples with a reference chronology are introduced: (i) calculating confidence intervals around the LOESS-smoothed Δ14C reference chronology using simultaneous inference; (ii) purposely adding biases to the validation sample ages and then analyzing the sum of squared residuals of the validation samples’ Δ14C about the LOESS-smoothed reference chronology; and (iii) standardizing the Δ14C measurements from the validation sample to better fit the reference chronology. Standardized Δ14C measurements are particularly useful when researchers suspect that environmental and biological differences between the validation samples and the reference chronology may exist that affect the level, but not the timing, of Δ14C in the samples. These new methods can be applied simultaneously. Two previous bomb radiocarbon studies on canary rockfish ( Sebastes pinniger ) and black drum ( Pogonias cromis ) were reanalyzed, further illustrating the usefulness of these new methods.
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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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".