Bibliographic record
Abstract
BMK-DKO cells expressing CBcl-W, transfected with VBH3 proteins treated with BH3 mimetics. Data displayed in Figure 5a-d was generated from combining results of 4 screens: 1) mim1_BclW_screen {Rep1_20190212, Rep2_20190213, Rep3_20190214, Rep4_20190215} 2) mim2_BclW_screen {Rep1_20190403, Rep2_20190404, Rep3_20190405, Rep4_20190406} 3) XL2W_screen {Rep1_20191108, Rep2_20191109, Rep3_20191110, Rep4_20191111} Figure 5f-g was generated from BH3 swap screen {Rep1_20200821, Rep2_20200827, Rep3_20200902, Rep4_20200904} -For each screen, see "Master Platemap" for screen design as well as data generated in qF3 analysis step 8_CombineBinnedReps: Here are, "combined_WellID_binnedReps_.csv" data files, that were fit to determine live cell Kds. Exported result from fitting these data is also included in, "CombinedBinnedReps_Results.xlsx". -Figure 5a-c shows the average of controls (VBH3 proteins and corresponding collisional control: VBH3-4E) included in each of these screens. (See "Summarized_CBclW_ Results.xlsx").
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.607 | 0.378 |
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".