MAU2 is required for zebrafish neurodevelopment
Bibliographic record
Abstract
Front cover -Two smiles, one hope Six-year-old Mattia has Wilson's disease, a radiant smile, and a new friend: researcher Pasquale Piccolo, who leads a team at the Telethon Institute of Genetics and Medicine (Tigem) focused on gene therapy for the liver, aiming to combat Mattia's disease.Immagine di copertina -Due sorrisi, una speranza Mattia, sei anni, ha la malattia di Wilson, un sorriso contagioso e un nuovo amico: il ricercatore Pasquale Piccolo, che all'Istituto Telethon di Genetica e Medicina (Tigem) guida un gruppo di lavoro sulla terapia genica diretta al fegato, per combattere per esempio la malattia di Mattia.Grafica e stampa / Design and print: Gattinoni & Co Srl 12 marzo 2025 / March 12, 2025 "Un buon esempio non è quello che insegniamo agli altri, ma quello che fanno gli altri con il nostro esempio" Nelson MandelaDesideriamo esprimere un sincero ringraziamento a tutti gli organizzatori, sostenitori e partecipanti, che hanno reso possibile questa XXII Convention di Fondazione Telethon ETS.Il lavoro dei ricercatori, costante e instancabile, è un esempio di come l'impegno possa generare risultati tangibili, costruendo un futuro migliore per le persone con malattie genetiche rare, che con speranza attendono risposte, vigilando sul loro operato.Grazie di cuore a tutti per il vostro prezioso contributo e le vostre testimonianze. "A good example is not what is taught to others, but what others do with our example" Nelson MandelaWe would like to express our sincere thanks to all the organizers, supporters, and participants who made this XXII Convention of the Telethon Foundation ETS possible.The work of the researchers, constant and tireless, is an example of how commitment can generate tangible results, building a better future for people with rare genetic diseases, who, with hope, await answers, closely following the progress of their work.A heartfelt thank you to everyone for your valuable contribution and your testimonies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".