Bibliographic record
Abstract
Figure 2 data Includes: -Panel B, colocalization data. Pearson's correlation values were exported per cell in Cell Profiler, then minimum intensity thresholds were applied to ensure the cells were stained/expressing the protein(s) of interest. Here is the resulting summary where we exported the median and mode of each set of data. -Panel C- F, FLIM-FRET data acquired for one biological replicate acquired where date acquired, Cell line, and mCerulean3-donor is given within each Excel worksheet. Raw binding curve data was binned by Venus intensity. Here we provide the resulting binned data, and fitting parameters exported from GraphPad prism used to create the binding curves that were displayed in the paper. The remaining biological replicates are uploaded with "OsterlundJBC_SFigure 2". -Panel G, Cell death measured in MCF-7 cells and MCF-7 cells expressing mCerulean3-tagged BCL-2 or BCL-XL. Raw data were binned by Venus intensity. Here we provide the resulting binned data from 3 biological replicates, and the fitting parameters exported from GraphPad prism for curves displayed in the paper. -Panel H, Cell death measured in HEK293T cells. AnnexinV positivity is a marker of Cell death. Here we provide the mean cell death measured in Venus positive cells from 3 biological replicates.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.814 | 0.680 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".