Characterization of translational regulation during long-term facilitation in «Aplysia»
Bibliographic record
Abstract
Compartment-specific, differential regulation of eukaryotic elongation factor 2 and its kinase within Aplysia sensory neurons.I helped perform the experiment presented in Figure 3-2A, performed all other experiments, carried out all of the quantitation and analysis of the data, constructed all figures except Figure 3-1, and wrote most of a draft of the manuscript.Eugenia Pethoukov made and purified the eEF2K antibodies and performed the experiment in Figure 3-2A.Together, Xiaotang Fan, Matthew Carroll, Dana Murchison, Emilie Belley, and Andrew Heppner cloned Aplysia eEF2K and generated the eEF2K(WT) and eEF2K(S454A) baculovirus transfer and Aplysia expression constructs.Xiaotang Fan also transfected Sf9 cells in order to generate high titer baculoviruses.Wayne Sossin provided guidance in designing experiments, performed bioinformatics on eEF2K, made Figure 3-1, and commented on and helped revise a draft of the manuscript.
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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) | 0.001 | 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 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".