Bibliographic record
Abstract
Cristina Dallabona, Truus E. M. Abbink, Rosalba Carrozzo, Alessandra Torraco, Andrea Legati, Carola G. M. van Berkel, Marcello Niceta, Tiziana Langella, Daniela Verrigni, Teresa Rizza, Daria Diodato, Fiorella Piemonte, Eleonora Lamantea, Mingyan Fang, Jianguo Zhang, Diego Martinelli, Elsa Bevivino, Carlo Dionisi-Vici, Adeline Vanderver, Sunny G. Philip, Manju A. Kurian, Ishwar C. Verma, Sunita Bijarnia-Mahay, Sandra Jacinto, Fatima Furtado, Patrizia Accorsi, Anna Ardissone, Isabella Moroni, Ileana Ferrero, Marco Tartaglia, Paola Goffrini, Daniele Ghezzi, Marjo S. van der Knaap and Enrico Bertini. LYRM7 mutations cause a multifocal cavitating leukoencephalopathy with distinct MRI appearance. Brain 2016; 139: 782-794. doi:10.1093/brain/awv392. The authors apologize for mixing the mutations of Patients 5 and 7 on pages 788 and 789 in Figure 2 and its legend, in the main text and the online Supplementary Tables. This has now been corrected online. On page 788, the text should read: Sanger sequencing of the entire coding sequence of LYRM7 and intron-exon boundaries was performed in three additional patients. Patient 5 was found homozygous for the c.37delA (p.Thr13Hisfs∗17) mutation, which is predicted to dramatically affect recognition of the splice donor motif of exon 4 and likely impair proper RNA splicing (Fig. 2M and N), while Patients 6 and 7 were found to be homozygous for the c.214C4T (p.Q72∗) (Fig. 2L), and c.243-244 + 2delGAGT (p.?) (Fig. 2H) mutations, respectively. The Supplementary Tables have been corrected online. On page 789, Figure 2 and legend should be as follows.
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.460 | 0.341 |
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".