Two-stage Sampling on Additive Model for Quantitative Sensitive Question Survey and Its Application
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
Objective To explore scientific sampling methods and corresponding formulas for quantitative sensitive question survey on two-stage random sampling. To provide scientific data for the prevention and control of high risk AIDS population in Beijing. Methods Additive model for quantitative sensitive question survey, two-stage random sampling, properties of variance and mean were used. Results Formulas for the esti¬mation of the population proportions and its variance on additive model for quantitative sensitive question survey were deduced. The survey methods and formulas were employed successfully in the survey of the age of the first time when MSM having sex with men and the result was 21.9747. Conclusion The methods and corresponding formulas for two-stage sampling on additive model for quantitative sensitive question survey are feasible. Key words: Sensitive questions; Additive model for randomized response technique; Two-stage sampling; MSM
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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 | 0.003 | 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 | 0.000 | 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