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Enregistrement W1606959122 · doi:10.18438/b8c908

Neuroscientists’ Domain Knowledge Does Not Improve Search Performance in PubMed

2010· article· en· W1606959122 sur OpenAlexvenueno aff
Giovanna Badia

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2010
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueAcademic Writing and Publishing
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSession (web analytics)Task (project management)MEDLINEComputer sciencePsychologyDomain (mathematical analysis)World Wide Web

Résumé

récupéré en direct d'OpenAlex

A Review of: Vibert, N., Ros, C., Le Bigot, L., Ramond, M., Gatefin, J., & Rouet, J.-F. (2009). Effects of domain knowledge on reference search with the PubMed database: An experimental study. Journal of the American Society for Information Science and Technology, 60(7), 1423-1447. Objective – To determine whether neuroscientists and life scientists’ domain knowledge affects their search performance in PubMed for neuroscience topics. Design – Cross-sectional experimental study. Setting – State-funded research laboratories in the cities of Paris, Bordeaux and Poitiers, France. Subjects – There were 32 participants in the study: 16 neuroscientists and 16 life scientists with no experience in neuroscience. Both groups were similar in terms of age, gender, occupation, and online database search experience. Methods – All participants were asked to complete the same five tasks in PubMed to assess their search performance with this database. Each task consisted of finding and selecting bibliographic references on a neuroscience topic within 15 minutes. The instructions for these tasks were hidden from view during the search process. Participants performed the tasks on their office computers between May 2005 and June 2006 in the presence of one researcher who prompted them to verbally describe what they were doing and thinking as they searched. Each participant also filled out a questionnaire about their personal characteristics at the beginning of the search session and completed a second questionnaire about their knowledge of PubMed at the end. The entire experimental procedure lasted between 60 and 90 minutes and was recorded. The relevancy of the bibliographic references selected was later scored by two neuroscientists who did not participate in the study. The data were analyzed using multivariate analysis of variance (MANOVA) and qualitative analysis of verbal protocols. Main Results – The MANOVA analysis did not show any significant differences between the total scores obtained by the neuroscientists and the life scientists. Both groups were able to find relevant PubMed references for each task within the time allotted. Contrary to the researchers’ first main hypothesis, the neuroscientists’ domain knowledge did not result in a superior search performance (i.e., in less time spent searching and more relevant results) compared to that of the life scientists. However, domain knowledge did affect the method of searching, confirming the researchers’ second hypothesis. The life scientists spent more time reading the instructions for each task, included more keywords in their search queries, and opened more abstracts to select relevant references than the neuroscientists. The life scientists also used keywords that were almost exclusively taken from the instructions for each task when they searched PubMed and made significantly more mistakes than the neuroscientists. Furthermore, the participants’ knowledge of PubMed was poor as was expected, despite stating they used it very frequently. Half of the participants did not attempt to use limits even when the task called for it. The majority only used PubMed in the most basic way, that is, by typing keywords in the search box. Conclusion – Domain knowledge affects how end users search PubMed for topics in their specialty, but it does not impact their performance. Both the neuroscientists and the life scientists successfully completed the search tasks on neuroscience topics within the allotted time. Both groups had basic knowledge of PubMed, but were satisfied with their performance and results. The authors suggest that scientists would only be interested in attending a PubMed training session if they are convinced that they will learn how to search more quickly. Further experiments are needed to verify the effects of domain knowledge on search performance with topics that are more general. The search tasks used in this study were very specific, which may have positively influenced the performance of all participants. A different control group that shares less basic domain knowledge with the neuroscientists, such as mathematicians or chemists, may also be tested.

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)0,006
score de la tête « metaresearch » (Gemma)0,078
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,994
Score d'incertitude au seuil0,030

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,078
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0030,004
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,002

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 Opus0,021
Tête enseignante GPT0,244
Écart entre enseignants0,223 · 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
DomaineMéthodes
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
Publié2010
Routes d'admission1
Résumé présentoui

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