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Enregistrement W1857591936 · doi:10.1097/01.asm.0001073532.48104.42

Showcasing Science in San Diego

2015· article· en· W1857591936 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueASA Monitor · 2015
Typearticle
Langueen
DomainePsychology
ThématiqueScience Education and Perceptions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEngineering

Résumé

récupéré en direct d'OpenAlex

Joy L. Hawkins, M.D., is Professor of Anesthesiology, Vice Chair for Education and Director of Obstetric Anesthesia, University of Colorado School of Medicine, Aurora.The ANESTHESIOLOGY® annual meeting provides many educational opportunities for ASA members and attendees. As a part of the meeting each year, FAER hosts a number of sessions that aim to inspire and prepare physician anesthesiologists to pursue new knowledge and advance patient care through anesthesiology, perioperative, health services and medical education research. The events recognize excellence in research and mentoring while serving to educate and advance the scientific talent in anesthesiology. If you are attending the ANESTHESIOLOGY® 2015 annual meeting in San Diego, I encourage you to check out any number of FAER’s or other scientific sessions that demonstrate the many avenues in which anesthesiologists are driving medical progress, and can continue to do so in the future. FAER Mentoring Excellence in Research Award: David S. Warner, M.D. The research mentors who develop and guide early career physician scientists ultimately shape the future of the specialty, medicine and patient care. Each year at the ANESTHESIOLOGY® annual meeting, the FAER Academy of Research Mentors in Anesthesiology presents its Mentoring Excellence in Research Award during the Celebration of Research. This honor acknowledges those who have not only dedicated their careers to scientific discovery but also have developed the careers of others who will do the same.David S. Warner, M.D.The recipient of the 2015 FAER Mentoring Excellence in Research Award is David S. Warner, M.D., Vice Chair of Research, Chief, Division of Basic Sciences, Distinguished Professor of Anesthesiology, Professor in Neurobiology and Professor of Surgery at Duke University School of Medicine in Durham, North Carolina. “Dr. Warner is an outstanding scientist who has published more than 250 peer-reviewed papers, a distinguished professor with appointments in three different departments at Duke (anesthesiology, surgery and neurobiology), and a skilled clinician who regularly provides top-notch care for patients,” said Miles Berger, M.D., Ph.D., Assistant Professor in Neuro-anesthesia at Duke University, who nominated Dr. Warner for the award. “Perhaps Dr. Warner’s greatest accomplishment, and his most lasting legacy, will be the nearly 80 post-doctoral trainees and students he has mentored over his nearly 40-year career as a physician scientist.” Dr. Warner’s trainees represent such academic institutions as Stanford University, University of Washington in Seattle, University of Colorado, Denver, Washington University in St. Louis, Yale University, University of Manitoba in Canada, Yamaguchi University in Japan and many more. He is an outstanding physician scientist whose mentorship has been supported by a National Institutes of Health training grant (NIH T32) for the past 19 years. “The driving force behind this nearly unsurpassed record of mentorship is Dr. Warner’s love of science, and his passion for mentoring young trainees,” Dr. Berger said. “When Dr. Warner discusses science, his eyes brighten, his mood livens and his passion for science becomes clear. This passion for science is matched by serious intellectual rigor – Dr. Warner pays close attention to ensuring that experiments are carefully controlled and properly blinded.” Please join us in congratulating Dr. Warner and recog-nizing his achievements during the Celebration of Research, Monday, October 26, 9:35-11:05 a.m. in room Upper 20D.FAER Helrich Research Lecture: “Can We Do Better? How Big Data Can Help” Since 2001, the FAER Helrich Research Lecture, formerly the FAER Honorary Research Lecture, has recognized outstanding scholarship by a scientist in an effort to encourage young physician anesthesiologists to consider careers in research and teaching.Laurent G. Glance, M.D.Next month in San Diego, Laurent G. Glance, M.D. will discuss big data and how it can help physician anesthesiologists improve health care delivery during the 15th annual FAER Helrich Research Lecture. Dr. Glance is Professor and Vice-Chair for Research in the Department of Anesthesiology, and Professor of Public Health Sciences at the University of Rochester School of Medicine in Rochester, New York. He is also a Senior Scientist (adjunct) at RAND Corporation. The goal of Dr. Glance’s lecture is to help gain a better understanding of how big data can help physician anesthesiologists and surgeons improve surgical outcomes. He will describe the drivers for health care reform and the shift from volume-based reimbursement to value-based purchasing. He will also discuss the role of quality measurement in driving quality improvement and realigning incentives to improve population health, as well as the role of big data in filling the holes in evidence-based medicine. Please join us at the FAER Helrich Research Lecture, Monday, Oct. 26, 1:10-2:10 p.m., in Hall H.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,233
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,002

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.

Tête enseignante Opus0,174
Tête enseignante GPT0,458
Écart entre enseignants0,284 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle