Notice bibliographique
Résumé
“If you want to make an impact among your colleagues, look especially at the journals that they’re reading and publishing in” Dr H Goldman, Chief Editor of Polar Research Writing medical articles is highly competitive. Many hours are expended conducting research, and even more hours writing and rewriting the manuscript. Furthermore, countless hours are spent chasing references and performing complex statistics. However, when it comes to understanding the target audience, are authors guilty of not investing as much effort to get maximum impact from the fruits of their labour? The issue of where to send your manuscript has never been more critical. Most clinicians receive daily invitations via email to submit work to journals that sound legitimate and valid. But are they? Although many journals are reputable, many others are not. This stems partly from the sharp decline in paper journals and the parallel exponential rise in digital journals. With intense pressure to publish, it is hard not to be seduced by online journal marketing ploys. For instance, one researcher used www.randomtextgenerator.com to make up an article and submitted it to 37 open access journals over a period of 2 weeks. 1 At least 17 accepted his work and agreed to publish his article once a $500 ‘processing fee’ had been paid. Investing time and effort in ‘where to publish’ is time well spent. It is an exercise in understanding the target audience that will benefit most from the publication. Doing this at an early stage in the publishing process saves valuable time and resources. More importantly, this increases the chances of acceptance. So what are the tips for checking journal legitimacy and avoiding the trap of predatory journals? > Check the journal website and look through a recent issue. > Is the journal indexed? Check journal databases like PubMed Central® or the Web of Science®. Is there a link on the journal web pages to the spoof www.medline.com ? > Check the name of the editor-in-chief and associated board members. > Check the registered address on Google Maps®. > Have your colleagues and friends read, reviewed or published in the journal? > Is the journal identified in Jeffrey Beall’s list of potential predatory journals? 2 Finally, a word about blogs and social media. As the internet revolutionises the whole business of publishing and makes information easy to access, are blogs and self-publishing a way forward for scholarly publications? Such open narratives encourage comments and dialogue with readers, leading to an open and transparent form of peer review. This process itself leads to change, revision and expansion. Is this the future? In this article, Anna Sharman, who launched Cofactor in 2014, provides readers with some useful insights into where to publish. Anna did a PhD degree in biology and then entered the world of journal publishing. She worked for publishers such as BMJ, Public Library of Science, BioMed Central and Nature Publishing Group. Her latest venture, Cofactor, is a company that offers editing advice and training for scientific researchers to help them publish their work more effectively. JYOTI SHAH Commissioning Editor References 1. Why a fake article titled ‘Cuckoo for cocoa puffs?’ was accepted by 17 medical journals . Fast Company. http://www.fastcompany.com/3041493/body-week/why-a-fake-article-cuckoo-for-cocoa-puffs-was-accepted-by-17-medical-journals (cited May 2015 ). 2. List of Standalone Journals . Scholarly Open Access . http://scholarlyoa.com/individual-journals/ (cited May 2015 ).
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».