Bibliographic record
Abstract
The editors and Karger Publishers would like to thank the following reviewers for their ongoing support in reviewing manuscripts for Neurodegenerative Diseases:Birol Ay, Boston, MA, USATim Bathe, Munich, GermanyJulian Benito-Leon, Madrid, SpainDaiana Bezzini, Siena, ItalyCecilia Boccalini, Geneva, SwitzerlandMarina Boccardi, Rostock, GermanyStephan Bohlhalter, Lucerne, SwitzerlandKota Bokuda, Tokyo, JapanGiulia Bommarito, Lausanne, SwitzerlandMiguel G. Borda, Stavanger, NorwayStéphanie Borel, Paris, FranceDaniele Botta, Geneva, SwitzerlandRachel Buckley, Cambridge, MA, USAChuanhai Cao, Tampa, FL, USAStefano F. Cappa, Pavia, ItalyVasilios C. Constantinides, Athens, GreecePatrizia D'Amelio, Lausanne, SwitzerlandKensuke Daida, Tokyo, JapanLuc Defebvre, Lille, FranceArnaud Delval, Lille, FranceTalha Bin Emran, Chittagong, BangladeshChih-Hsiang Fang, Taipei, TaiwanAnsgar Felbecker, Bern, SwitzerlandSol Fittipaldi, Buenos Aires, ArgentinaThomas Gasser, Tübingen, GermanyAli Ghanem, Dallas, TX, USAYihan Hu, Stockholm, SwedenSaravanan Jagadeesan, Klang, MalaysiaQing Jiang, Nanjing, ChinaMario Jreige, Lausanne, SwitzerlandKazuya Kawabata, Toyoake, JapanDouglas H. Kelley, Rochester, NY, USASanjeev Kumar, Toronto, ON, CanadaRichard Lathe, Edinburgh, UKJae-Hong Lee, Seoul, Republic of KoreaJonathan F. Lovell, Buffalo, NY, USAJanet Maccora, Oxford, UKVincent Martel-Sauvageau, Quebec City, QC, CanadaAlessandro Martorana, Torre Gaia, ItalyJuan J.G. Meilán, Salamanca, SpainPedro Modrego, Zaragoza, SpainEric Morel, Lausanne, SwitzerlandYuki Mori, Copenhagen, DenmarkYasmin K. Nasr-Eldin, Minya, EgyptAbubakar Nazir, Lahore, PakistanMaiken Nedergaard, Copenhagen, DenmarkAneeqa Noor, Islamabad, PakistanLuc Nwamekang Belinga, Lausanne, SwitzerlandJavier Oltra, Stockholm, SwedenMarkus Otto, Halle, GermanyLorenzo Pini, Brescia, ItalyEmanuele Plini, Dublin, IrelandYothin Rakvongthai, Bangkok, ThailandRamin Rasi, Istanbul, TurkeyTimothy Rittman, Cambridge, UKFrancisca Rodriguez, Greifswald, GermanyMarco Romanato, Paris, FranceMartha C. Rosales Hernandez, Mexico City, MexicoAmber Ruigrok, Manchester, UKWataru Sako, Tokushima, JapanKatsuya Satoh, Nagasaki, JapanLouise Schindler, Lausanne, SwitzerlandPetra Schwingenschuh, Graz, AustriaAriana Stickel, San Diego, CA, USAJorge Storniolo, Piancavallo, ItalyJorge Suárez-Medellín, Xalapa, MexicoSivaniya Subramaniapillai, Lausanne, SwitzerlandBogdan-Ionel Tamba, Iasi, RomaniaMarco Toccaceli Blasi, Rome, ItalyMartina Valletta, Stockholm, SwedenTianhao Wang, Chicago, IL, USAEmma Weltings, Amsterdam, The NetherlandsKarolina A. Wojtunik-Kulesza, Lublin, PolandLiyong Wu, Beijing, ChinaKathryn A. Wyman-Chick, Minneapolis, MN, USA
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 | 0.021 | 0.212 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.276 | 0.193 |
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".