www.statassoc.or.th Contributed paper Inference Concerning the Conversion Efficiency for a Special Predator-prey System
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Bibliographic record
Abstract
In this communication, we consider the inference problem for the ratio of two interaction parameters, the so-called conversion efficiency of the Lotka-Volterra ordinary differential equations system (ODEs). The stochastic model under consideration views the actual population sizes as random perturbations of the solutions to these ODEs. Namely, we assume that the perturbations follow correlated Ornstein-Uhlenbeck processes and thus, no assumption is made that the random variables are independent. In this context, we establish the uniformly most powerful unbiased test for the conversion efficiency parameter. The asymptotic properties of the proposed test are derived. A simulation study is conducted and this provided strong evidence that corroborates with the usual asymptotic theory of optimal tests. To illustrate the procedure, the proposed method is applied to the Canadian mink-muskrat data set. ______________________________
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it