Lake Roosevelt White Sturgeon Modeling Support
Bibliographic record
Abstract
This report contains summarized progress on the construction, validation, and calibration of a hydrodynamic and water temperature model, and individual-based sturgeon model, for the Transboundary Reach of the Columbia River and Lake Roosevelt. A 1-dimensional hydrodynamic and water temperature model, the Modular Aquatic Simulation System in 1-dimension (MASS1), was constructed using existing bathymetry data from the U.S.-Canada international border to Grand Coulee Dam, and validated using velocity, temperature, and water elevation data collected by staff of the CTCR during three distinct hydrodynamic periods occurring in early spring, late spring, and summer in the study area. Parameters of MASS1 were then calibrated so that model simulations matched empirical data of water surface elevations collected in 2016. Several years of MASS1 data were archived and are available for use with the sturgeon IBM: 1975–2001, 2004, 2005, 2007–2015, and April–August 2016. An individual-based simulation model was concomitantly constructed to simulate four of the early life stages of white sturgeon: spawning, embryo incubation, free embryos, and early larvae. Submodels for each of the four life stages contain mathematical algorithms that primarily describe the growth, development, and movement of individuals based on outputs from MASS1. Sturgeon simulations were then run for two historical years where limited recruitment may have occurred (1997 and 2011) and two years in which recruitment likely did not occur (2004 and 2005).
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".