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Enregistrement W3017759854 · doi:10.1101/2020.04.27.063578

A systematic examination of preprint platforms for use in the medical and biomedical sciences setting

2020· preprint· en· W3017759854 sur OpenAlexafffund
Jamie J Kirkham, Naomi Penfold, Fiona Murphy, Isabelle Boutron, John P. A. Ioannidis, Jessica Polka, David Moher

Notice bibliographique

RevuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Langueen
DomaineDecision Sciences
ThématiqueAcademic Publishing and Open Access
Établissements canadiensOttawa HospitalUniversity of Ottawa
Organismes subventionnairesMedical Research CouncilCanadian Institutes of Health ResearchEuropean CommissionWellcome Trust
Mots-clésPreprintDiscoverabilityScope (computer science)World Wide WebMetadataComputer scienceBusiness

Résumé

récupéré en direct d'OpenAlex

ABSTRACT Objectives The objective of this review is to identify all preprint platforms with biomedical and medical scope and to compare and contrast the key characteristics and policies of these platforms. We also aim to provide a searchable database to enable relevant stakeholders to compare between platforms. Study Design and Setting Preprint platforms that were launched up to 25 th June 2019 and have a biomedical and medical scope according to MEDLINE’s journal selection criteria were identified using existing lists, web-based searches and the expertise of both academic and non-academic publication scientists. A data extraction form was developed, pilot-tested and used to collect data from each preprint platform’s webpage(s). Data collected were in relation to scope and ownership; content-specific characteristics and information relating to submission, journal transfer options, and external discoverability; screening, moderation, and permanence of content; usage metrics and metadata. Where possible, all online data were verified by the platform owner or representative by correspondence. Results A total of 44 preprint platforms were identified as having biomedical and medical scope, 17 (39%) were hosted by the Open Science Framework preprint infrastructure, six (14%) were provided by F1000 Research Ltd (the Open Research Central infrastructure) and 21 (48%) were other independent preprint platforms. Preprint platforms were either owned by non-profit academic groups, scientific societies or funding organisations (n=28; 64%), owned/partly owned by for-profit publishers or companies (n=14; 32%) or owned by individuals/small communities (n=2; 5%). Twenty-four (55%) preprint platforms accepted content from all scientific fields although some of these had restrictions relating to funding source, geographical region or an affiliated journal’s remit. Thirty-three (75%) preprint platforms provided details about article screening (basic checks) and 14 (32%) of these actively involved researchers with context expertise in the screening process. The three most common screening checks related to the scope of the article, plagiarism and legal/ethical/societal issues and compliance. Almost all preprint platforms allow submission to any peer-reviewed journal following publication, have a preservation plan for read-access, and most have a policy regarding reasons for retraction and the sustainability of the service. Forty-one (93%) platforms currently have usage metrics, with the most common metric being the number of downloads presented on the abstract page. Conclusion A large number of preprint platforms exist for use in biomedical and medical sciences, all of which offer researchers an opportunity to rapidly disseminate their research findings onto an open-access public server, subject to scope and eligibility. However, the process by which content is screened before online posting and withdrawn or removed after posting varies between platforms, which may be associated with platform operation, ownership, governance and financing. What is already known on this topic In concurrence with an increase in the number of preprint servers and platforms supporting biomedical and medical sciences research since 2013, there has been substantial growth in the number of preprints posted in this research area. The significant benefits of accelerated dissemination of research that preprints offer has attracted the support of many major funders. The raised profile of preprints has led to their wider acceptance in institutional and individual level assessment. What this study adds This is the first full examination of the characteristics and policies of 44 preprint platforms with biomedical and medical scope. We use a robust methodological approach to extract relevant information from web-based material with input from preprint platform owners. Despite concerns regarding the permanence and quality of preprints, most preprint platforms have long-term preservation strategies and many have screening checks (for example, a basic check for the relevance of content) in place. For some platforms, these checks are performed by researchers with content expertise. We provide a searchable database as a valuable resource for researchers, funders and policymakers in the biomedical and medical science field to determine which preprint platforms are relevant to their research scope and which have the functionality and policies that they value most.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,050
score de la tête « metaresearch » (Gemma)0,252
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Communication savante, Science ouverte
Catégories consensuellesaucune
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,998
Score d'incertitude au seuil0,263

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0500,252
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0240,021
Études des sciences et des technologies0,0010,002
Communication savante0,0050,006
Science ouverte0,0020,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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 Opus0,082
Tête enseignante GPT0,341
Écart entre enseignants0,259 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineÉvaluation
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

Citations37
Publié2020
Routes d'admission2
Résumé présentoui

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