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
The isolation of nuclei is often the first step in studying processes such as nuclear-cytoplasmic shuttling, subcellular localization of proteins, and protein-chromatin or nuclear protein-protein interactions in response to diverse stimuli. Therefore, rapidly obtaining nuclei from cells with relatively high purity and minimal subcellular contamination, protein degradation, or postharvesting modification is highly desirable. Historically, the isolation of nuclei involved a homogenization step followed by centrifugation through high-density glycerol or sucrose. Although clean nuclei with little cytoplasmic contamination can be prepared using this method, it is typically time consuming and can allow protein degradation, protein modification, and leaching of components from the nuclei to occur. We have developed a rapid and simple fractionation method that is based on the selective dissolution of the cytoplasmic membrane (but not the nuclear membrane) using a low concentration of a nonionic detergent and rapid centrifugation steps. Here we describe important considerations when isolating nuclei from cells, introduce our rapid method, and compare this method to a more traditional protocol for isolating nuclei, noting the strengths and limitations of each approach.
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