Purification of the N-HEAT_81-1643_Additional Heparin step
Bibliographic record
Abstract
Previously, I purified the HTT N-HEAT_81-1643 domain and showed that the HTT N-HEAT_81-1643 domain also elutes early from a Superose 6 column 10/300 (https://zenodo.org/record/3462496#.XY4limYpA2x). One hypothesis we proposed that could explain the early elution volume is that the construct HTT N-HEAT_81-1643 forms a complex with nucleic acid material. Here we added an additional purification step with heparin resin to remove nucleic acid material from the sample. This strategy was successful for full length HTT+HAP40 samples in removing nucleic acid and other impurities from the samples (https://zenodo.org/record/2628064#.XYTL7WYpDcs) (performed by Dr. Rachel Harding). Purified HTT N-HEAT_81-1643 domain sample was used to perform a buffer screen and biophysical characterization with DSLS, DSF and DLS.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.050 |
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".