Additional file 23 of Unexpected organellar locations of ESCRT machinery in Giardia intestinalis and complex evolutionary dynamics spanning the transition to parasitism in the lineage Fornicata
Bibliographic record
Abstract
Additional file 23: Additional Material 23-Supplementary Figure 9. Crude sub-cellular fractionation analysis of HA-GiCHMP7. HA-GiCHMP7-expressing transgenic trophozoites and non-transgenic control cells were subject to crude subcellular fractionation experiments through a freeze-thaw approach in liquid nitrogen to separate membrane-enriched and soluble fractions. Crudely fractionated protein samples, along with whole cell lysates from HA-GiCHMP7 transgenic lines and WB cells as a non-transgenic negative control, were subject to blotting for immuno-detection using an anti-HA antibody, followed by a secondary anti-Rat antibody coupled to HRP. A separate Coomassie gel was also prepared and depicted to demonstrate comparable amounts of protein were loaded for detection. The full experimental approach is reported in the Methods section. M: Marker; WB: non-transgenic total lysate; WCL: whole cell lysate; F-S: crudely-fractionated sample enriched for soluble components; F-M: crudely-fractionated sample enriched for membrane components.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.883 | 0.290 |
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".