Notice bibliographique
Résumé
It is a great pleasure to announce that the Journal of Nursing Research (JNR) has stepped into its 6th year since being indexed in both the Journal of Citation Report/Science Edition (SCI) and Social Science Edition (SSCI). JNR is the official journal of the Taiwan Nurses’ Association (TWNA). In order to better advance and inspire active interactions and scientific inquiry within and among the fields nursing, clinical practice, and nursing education, the journal began being published in English since 2001 and was successfully indexed in SCI and SSCI in 2012. Compared with many internationally recognized nursing journals, JNR is still in its infancy and growing. However, the continuous contribution and support of nursing researchers in Taiwan and internationally has led JNR to become one of the world’s most active nursing journals, attracting manuscript submissions from nursing researchers around the world. Furthermore, JNR‘s online edition continues to enjoy a rapidly increasing readership in both Western and Eastern countries, with the United States and Taiwan, respectively, providing JNR’s first and second largest readership, followed by Turkey, the UK, Iran, Australia, Canada, India, China, and South Korea. Both submission and research data support the important role of JNR in facilitating knowledge dissemination as well as reaffirm the journal’s scientific quality and value as an academic nursing journal. JNR is committed to further enhancing the growth and depth of evidence-based knowledge in nursing science, nursing education, and clinical practice. Therefore, the journal will be published as a bimonthly instead of a quarterly publication starting this year (2017). In addition to original articles, we will be publishing a larger number of reviews and perspective papers on important issues in nursing and healthcare in order to support our readers’ needs. Research to promote health and to overcome care problems, from acute to chronic and community care, will be addressed and discussed in JNR. Innovative studies that facilitate the performance of nursing education, nursing practice, and care-system quality represent important directions for the coming year and beyond. Furthermore, using high technology and informatics to enhance the quality of future care is a formative trend in healthcare and thus an important and growing target area for JNR’s scientific works. However, as always, qualitative inquiry that captures the precious living experiences in health and in illness will remain an important part of JNR as well. Finally, patient and nurse safety and violence-prevention issues are both important concerns in our daily practice and areas that deserve new knowledge and evidence-based improvement. JNR has built a solid foundation for disseminating nursing science over its first decade in English. We strongly believe that it will continue to grow and improve as an influential academic nursing journal, supporting the expansion of critical nursing knowledge and increased interactions among nurse clinicians, educators, students, and researchers as well as advancing nursing sciences and professionalism at multiple levels and across the healthcare spectrum.
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 | 0,001 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,651 | 0,451 |
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 ».