Bibliographic record
Abstract
The editors and Karger Publishers would like to thank the following reviewers for their ongoing support in reviewing manuscripts for Skin Appendage Disorders:Lorenzo Ala, Rome, ItalySarah Alsalman, Riyadh, Saudi ArabiaZoi Apalla, Thessaloniki, GreeceRoberto Arenas, Mexico City, MexicoDaniel Asz Sigall, Mexico City, MexicoEnzo Berardesca, Rome, ItalyRachel Berbert Ferreira, Maringá, BrazilRegina C. Betz, Bonn, GermanyAnna Campanati, Ancona, ItalyStephano Cedirian, Bologna, ItalySoumiya Chiheb, Casablanca, MoroccoEduardo Corona-Rodarte, Guadalajara, MexicoGeorge Cotsarelis, Philadelphia, PA, USALeandro Damiani, Porto Alegre, BrazilC. Ralph Daniel, Ridgeland, MS, USANilton Di Chiacchio, São Paulo, BrazilIsabella Doche, São Paulo, BrazilJudith Dominguez-Cherit, Tlalpan, MexicoAline Donati, São Paulo, BrazilJeffrey Donovan, Whistler, BC, CanadaHarold Farber, Philadelphia, PA, USAGustavo B.A. Faro, São Paulo, BrazilSteven R. Feldman, Winston-Salem, NC, USASimone Garcovich, Rome, ItalyMaria F.R.G. Gavazzoni Dias, Rio de Janeiro, BrazilNilton Gioia Di Chiacchio, São Paulo, BrazilFatih Göktay, Istanbul, TurkeyMohamad Goldust, Mainz, GermanyStamatios Gregoriou, Athens, GreeceChander Grover, Delhi, IndiaAditya K. Gupta, Toronto, ON, CanadaDaniela Guzmán-Sánchez, Guadalajara, MexicoEckart Haneke, Freiburg, GermanyHideo Hashizume, Iwata, JapanMolly A. Hinshaw, Madison, WI, USAShigeki Inui, Osaka, JapanDimitrios Ioannides, Thessaloniki, GreeceMatilde Iorizzo, Bellinzona, SwitzerlandNorito Ishii, Kurume, JapanTaisuke Ito, Hamamatsu, JapanFrancisco Jimenez, Las Palmas de Gran Canaria, SpainAwatef Kelati, Casablanca, MoroccoJonette E. Keri, Miami, FL, USANicolas Kluger, Helsinki, FinlandMariia Konchak, Lviv, UkraineManas Kshirsagar, Santa Cruz, CA, USAChanat Kumtornrut, Bangkok, ThailandMichelangelo La Placa, Bologna, ItalyFrancesco Lacarrubba, Catania, ItalyChinmanat Lekhavat, Bangkok, ThailandJeff Li, Coral Gables, FL, USAShari R. Lipner, New York, NY, USAKristen I. Lo Sicco, New York, NY, USANino Lortkipanidze, Tbilisi, GeorgiaSridhar Mani, New York, NY, USAMaría A. Martinez-Velasco, Mexico City, MexicoAmy J. McMichael, Winston-Salem, NC, USADaniel F. Melo, Rio de Janeiro, BrazilGiuseppe Micali, Catania, ItalyMariya Miteva, Miami, FL, USABrian Morrison, Miami, FL, USAIria Neri, Bologna, ItalyBetty Nguyen, Miami, FL, USAJorge Ocampo-Candiani, San Nicolás de los Garza, MexicoGeorgia Pappa, Athens, GreeceChristophe Perrin, Nice, FranceBianca M. Piraccini, Bologna, ItalyRodrigo Pirmez, Rio de Janeiro, BrazilChristos Prevezas, Athens, GreeceFrancesca Prignano, Florence, ItalyYuval Ramot, Jerusalem, IsraelMayra A. Reyes Soto, Monterrey, MexicoPhoebe Rich, Portland, OR, USAAlyx Rosen Aigen, Miami, FL, USALidia Rudnicka, Warsaw, PolandDavid Saceda-Corralo, Madrid, SpainAndrea Sechi, Milan, ItalyMaryanne M. Senna, Burlington, MA, USAYutaka Shimomura, Yamaguchi, JapanYehuda Shoenfeld, Tel Aviv, IsraelTatiana Silyuk, Saint Petersburg, RussiaRodney Sinclair, East Melbourne, VIC, AustraliaAsmahane Souissi, Tunis, TunisiaLeonard C. Sperling, Bethesda, MD, USAMichela Starace, Bologna, ItalyMariem Tabka, Sousse, TunisiaAnita Takwale, Gloucester, UKFrancesco Tassone, Rome, ItalyCurtis Thompson, Portland, OR, USADesmond Tobin, Dublin, IrelandJulio Torales, San Lorenzo, ParaguayNorma E. Vazquez-Herrera, Monterrey, MexicoStefano Veraldi, Milan, ItalyColombina Vincenzi, Bologna, ItalyKimberly N. Williams, Miami, FL, ChinaUwe Wollina, Dresden, GermanyXimena Wortsman, Santiago, ChileChao-Chun Yang, Tainan, TaiwanMartin Zaiac, Miami Beach, FL, USA
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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 | 0.021 | 0.230 |
| 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 | 0.018 | 0.011 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.263 | 0.188 |
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".