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2075 - Publication Rate of Podium Presentations from the 2012 - 2014 Orthopaedic Research Society Annual Meetings

2019· preprint· en· W4391532542 sur OpenAlexaboutno aff
Ayodeji Jubril, A. Michael

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineMedicine
ThématiqueMusculoskeletal Disorders and Rehabilitation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLibrary scienceComputer science

Résumé

récupéré en direct d'OpenAlex

Introduction: Annual scientific meetings serve as a forum for dissemination of new research findings. Presentations should be of high scientific quality as they have the potential to impact future research projects and current clinical practice. The publication rate of podium presentations at an annual meeting can be used to assess the quality of the research presented. The purpose of this study was to determine the publication rate of podium presentations at the 2012 u2013 2014 Orthopaedic Research Society (ORS) annual meetings.Methods: All podium presentations from the 2012 u2013 2014 ORS annual meetings were identified. A PubMed search was performed to determine if an abstract reached publication in a peer-reviewed journal. All podium presentations were categorized into a specific orthopaedic topic to determine if there were differences in the publication rate according to the topic. The journal of each full-text publication was identified, as well as the journal impact factor. The time to publication for each published abstract was calculated based on the date of the ORS meeting and the date of publication (rounded to the nearest month). The country and institution of origin of each full-text publication was also recorded.Results: There were a total of 1063 podium presentations at the 2012 u2013 2014 ORS annual meetings. Of these abstracts, 640 were subsequently published in a peer-reviewed journal for an overall publication rate of 60.2%. New Investigator Recognition Award (NIRA) podium presentations had an overall publication rate of 63.5%, though this was not significantly higher than the publication rate of non-recognized presentations at 59.8% (p = 0.5245). The orthopaedic topic with the greatest percentage of podium presentations was cartilage biology (27.1%), followed by bone biology (18.0%) and ligament/tendon biology (13.2%). Abstracts categorized as upper extremity had the highest publication rate (71.1%), followed by spine (66.7%) and bone biology (63.4%). Podium presentations were published in 151 different journals with the journal impact factor ranging from 0.56 to 39.24. The average impact factor for all of the published abstracts was 4.46. The top three most frequent journals for publication were Journal of Orthopaedic Research (10.6%), Journal of Biomechanics (5.2%), and PLoS ONE (5.2%). Time to publication varied significantly by journal (p = 0.025). The majority (75.9%) of abstracts that reached publication did so within 2 years. At 67.0%, the United States was the most common country of origin of all full-text publications, followed by Japan (10.9%) and Canada (3.6%). The top three academic institutions for publication were University of Pennsylvania (5.8%), Cornell University (3.6%), and Columbia University (3.4%). Discussion: The ORS annual meeting is a leading forum for the presentation of high-quality research in the field of surgery and musculoskeletal disease. In 1998, Daluiski et al. reported an overall publication rate of 52% for podium presentations at the 1991 u2013 1993 ORS annual meetings. To our knowledge, no studies evaluating the publication rate of ORS presentations have been conducted since that time. In our study, we found an overall publication rate of 60.2%, which is significantly higher than what was reported over two decades ago (p = 0.0004). This finding might suggest an improvement in the quality of research presented at the meeting. Furthermore, a rate of 60.2% is within the upper range of previously reported publication rates for other orthopaedic surgery meetings

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 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)0,003
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,881
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,036
Tête enseignante GPT0,365
Écart entre enseignants0,328 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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