Correction to “Early Nuclear Phenotypes and Reactive Transformation in Human <scp>iPSC</scp> ‐Derived Astrocytes From <scp>ALS</scp> Patients With <scp>SOD1</scp> Mutations”
Bibliographic record
Abstract
Vincent Soubannier1 2, Mathilde Chaineau1 2, Eric Deneault 1 2 4, Lale Gursu1 2, Sarah Lépine1 2, David Kalaydjian1 2, Julien Sirois1 2, Ghazal Haghi1 2, Guy Rouleau1, Thomas M Durcan1 2 3, Stefano Stifani1 4- New address: Centre for Oncology, Radiopharmaceuticals and Research (CORR), Biologic and Radiopharmaceuticals Drugs Directorate (BRDD), Health Products and Food Branch (HPFD), Health Canada, Ottawa, ON K1A 0K9, Canada An error in the author list led to the omission of Dr. Eric Deneault who helped generate the isogenic iPSCs used in this study. To correct this oversight, he is now included as an author in the corrected manuscript. We apologize for this error.
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 | 0.004 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.044 | 0.025 |
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".