Financial Disclosure Appendix for “Advances in Cleft Care”
Notice bibliographique
Résumé
EDITORS’ DISCLOSURES Editor-in-Chief: Kevin C. Chung, MD Dr. Chung is the Editor-in-Chief of Plastic and Reconstructive Surgery. He receives grants from the National Institutes of Health and book royalties from Wolters Kluwer and Elsevier. Guest Editors: Larry H. Hollier, Jr, MD; Richard A. Hopper, MD, MS; and Roberto L. Flores, MD Dr. Hollier is the chair of Smile Train’s Global Medical Advisory Board, a volunteer position. Drs. Hopper and Flores are members of Smile Train’s medical advisory board; these are volunteer positions. ARTICLE-BY-ARTICLE DISCLOSURES Bridging the Gap: Challenges and Opportunities for Advancing Cleft Nursing in Sub-Saharan Africa Vamsi C. Mohan, MD; Winston R. Owens, BS; and Rona J. Breese, BA, RGN Rona J. Breese is a nurse training consultant, educator, and curriculum developer in Africa and a member of Smile Train’s Global Medical Advisory Board, a volunteer position. The remaining authors have no financial interests to declare in relation to the content of this article. Improving Speech Outcomes in Low- and Middle-Income Countries for Patients Born with Cleft Palate Catherine J. Crowley, JD, PhD, CCC-SLP Dr. Crowley is a member of Smile Train’s Global Medical Advisory Board, a volunteer position. Optimizing Perioperative Anesthesia Protocols for Global Delivery of Safe Cleft Surgery Vamsi C. Mohan, MD; Winston R. Owens, BS; and Zipporah Gathuya, MD Dr. Gathuya is a board member of the Global Initiative for Children’s Surgery and a member of Smile Train’s Global Medical Advisory Board; these are volunteer positions. The remaining authors have no financial interests to declare in relation to the content of this article. Retrospective Review of Open Tip Plasty for Bilateral Cleft Nasal Deformity before Adolescent Growth: A Single Surgeon’s Experience of 25 Consecutive Cases Vamsi C. Mohan, MD; Winston R. Owens, BS; and Richard A. Hopper, MD, MS Dr. Hopper is a member of Smile Train’s Global Medical Advisory Board, a volunteer position. The remaining authors have no financial interests to declare in relation to the content of this article. Advances in the Prevention of Dental Caries in Orofacial Clefts Peter A. Mossey, BDS, PhD; Winston R. Owens, BS; Vamsi C. Mohan, MD; Elizabeth A. Shick, DDS, MPH; and Mónica Dominguez, DDS Dr. Mossey is a member of Smile Train’s Global Medical Advisory Board, a volunteer position. Dr. Dominguez is the director of global oral health programs for Smile Train. Dr. Shick is a volunteer consultant for Smile Train. The remaining authors have no financial interests to declare in relation to the content of this article. The Use of Technology in Improving Multidisciplinary Care in Low-Resource Settings Vamsi C. Mohan, MD; Winston R. Owens, BS; Pierce C. Hollier, BS; Solomon Obiri-Yeboah, MD, DDS; and Peter Donkor, MDSc Dr. Donkor is the president of the Ghana Cleft Foundation and a member of Smile Train’s Global Medical Advisory Board; these are volunteer positions. The remaining authors have no financial interests in any of the products, devices, or drugs mentioned in this article. Simulation in Cleft Care: Evolution, Evidence, and Training the Future Surgeon Allison L. Diaz, BS; Rami Kantar, MD, MPH, PhD; Dale J. Podolsky, MD, PhD; and Roberto L. Flores, MD Dr. Podolsky is a shareholder of Simulare Medical (Toronto, Ontario, Canada). No financial support was received from Simulare Medical for the preparation of this article. Dr. Flores is a member of Smile Train’s Global Medical Advisory Board, a volunteer position. The remaining authors have no financial interests to declare in relation to the content of this article. Cleft Presurgical Infant Orthopedics: Evolution from Analog to Digital Appliances—Will It Increase Accessibility? Winston R. Owens, BS; Vamsi C. Mohan, MD; Krishnamurthy Bonanthaya, MBBS; and Alvaro A. Figueroa, DDS, MS Drs. Figueroa and Bonanthaya are members of Smile Train’s Global Medical Advisory Board; these are volunteer positions. The remaining authors have no financial interests to declare in relation to the content of this article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,052 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,655 | 0,237 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».