Comparison of GAL80ts and Tet-off GAL80 transgenes
Bibliographic record
Abstract
, the UAS/GAL4 system has been instrumental in achieving spatial control, but the pursuit for the ideal system for temporal control is ongoing. One strategy used by many groups is to use GAL80. Two different kinds of GAL80 transgenic constructs have been reported but have never been compared directly. Here, we characterize and compare the repression ability of the GAL80ts and Tet-off GAL80 transgenes by two different assays. We found that GAL80ts was generally more efficient than Tet-off GAL80 and that the level of repression was dependent on the GAL4 driver, and did not necessarily correlate with expression level. We also investigated the level of expression upon inactivation of GAL80ts. The level and kinetics of inactivation were found to differ depending on the GAL4 driver and the stage of the life cycle, and in many cases the inactivation was incomplete. These results emphasize that it is essential to measure experimentally the level of expression under repressed and unrepressed states when multiple GAL4 drivers are used with GAL80 transgenes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".