<i>Sorting nexin‐14</i>, a gene expressed in motoneurons trapped by an in vitro preselection method
Bibliographic record
Abstract
A gene-trap strategy was set up in embryonic stem (ES) cells with the aim of trapping genes expressed in restricted neuronal lineages. The vector used trap genes irrespective of their activity in undifferentiated totipotent ES cells. Clones were subjected individually to differentiation in a system in which ES cells differentiated into neurons. Two ES clones in which the trapped gene was expressed in ES-derived neurons were studied in detail. The corresponding cDNAs were cloned, sequenced, and analysed by in situ hybridisation on wild-type embryo sections. Both genes are expressed in the nervous system. One gene, YR-23, encodes a large intracellular protein of unknown function. The second clone, YR-14, represents a sorting nexin (SNX14) gene whose expression in vivo coincides with that of LIM-homeodomain Islet-1 in several tissues. Sorting nexins are proteins associated with the endoplasmic reticulum (ER) and may play a role in receptor trafficking. Gene trapping followed by screening based on in vitro preselection of differentiated ES recombinant clones, therefore, has the potential to identify integration events in subsets of genes before generation of mouse mutants.
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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 | 0.000 | 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 | 0.001 |
| 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".