Bibliographic record
Abstract
I helped to improve the annotation of the Drosophila cadherin gene, Dcad87A, identified by the BDGP project. I generated polyclonal antibodies against Dcad87A and used these to analyze the protein distribution during embryogenesis and oogenesis. Dcad87A is mainly found in epithelial tissues. Subcellularly, Dcad87A is predominantly located on the apical membrane and in cytoplasmic vesicles. The distribution between the two subcellular pools is dynamically regulated during morphogenetic processes. Further, there is evidence that suggests that in some tissues Dcad87A is associated with microvilli. To gain an understanding of the function of Dcad87A, I employed different strategies to inactivate the gene function of Dcad87A. First, Dcad87A dsRNA was injected into embryos in order to silence Dcad87A. This did not produce a detectable embryonic or 1st instar larval mutant phenotype suggesting that Dcad87A may not be required for embryogenesis. I also designed and participated in the generation of RNA interference foldback constructs that will be used to silence Dcad87A postembryonically. Second, I analyzed lethal mutations that map to the chromosomal position of Dcad87A but found no evidence that one of those represents a mutation in Dcad87A. A sequence comparison revealed that the closest mammalian homologue to Dcad87A is cadherin23. Mutations of cadherin23 cause defects in the stereocilia (modified microvilli) of the hair cells of the inner ear, which leads to congenital deafness.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".