Bibliographic record
Abstract
BMK-DKO cells expressing CBcl-2, transfected with VBH3 proteins and treated with BH3 mimetics. This folder contains each binding curve plotted in STEP 10 of qF3 analysis. Filename includes information: "Well ID_Donor Fusion Protein_Transfectant_Treatment_Treatment concentration". Where a decimal in concentration is replaced with a dash in the filename. ie. 1.25uM is 1-25uM. The Filename of the file corresponds to the data plotted in Red. Positive and Negative controls (VBH3 and VBH3-4E) are plotted on each graph for comparison in Blue and Grey, respectively. If the data could be fit, then fit is displayed on the graph. Data displayed in Figure 3 was generated from combining results of 4 screens: 1) BclXL_Bcl2_screen {Rep1_20180822, Rep2_20180823, Rep3_20180830, Rep4_20180831} 2) mim2_Bcl2_screen {Rep1_20190326, Rep2_20190327, Rep3_20190328, Rep4_20190329} 3) XL2W_screen {Rep1_20191108, Rep2_20191109, Rep3_20191110, Rep4_20191111} 4) PumaV_screen {Rep1_20200909, Rep2_20200910, Rep3_20200916, Rep4_20200917} - see, "Figure 3" Dataset in dataverse for associated .CSV files for each binding curve.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.242 | 0.097 |
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".