A recurring error in evaluating the effects of different pesticides, pollutants and fertilizers with a zero level
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
Abstract Background The Quenouille-Addelman solution has been proposed to properly analyze linear models with a crossed or factorial arrangement of treatments that includes a qualitative/categorical and a quantitative factor with a zero level, a situation particularly prevalent in ecotoxicological studies. However, a review of the recent literature reveals that this solution isn’t used, perhaps due to a lack of recognition that zero-level factors can produce incomplete factorial arrangements. Results Using practical examples, I demonstrate that the conclusions of a study can be substantially altered if the Quenouille-Addelman solution is not used when warranted. Conclusions Suspecting that the lack of a detailed method may have contributed to the underutilization of the solution, I describe how to apply the solution using current statistical software packages and discuss how the solution can be adapted to address some experimental situations not previously considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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