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Using citation tracking for systematic literature searching - study protocol for a scoping review of methodological studies and an expert survey

2020· review· en· W3206940163 on OpenAlexaff
Julian Hirt, Thomas Nordhausen, Christian Appenzeller‐Herzog, Hannah Ewald

Bibliographic record

VenueF1000Research · 2020
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsCINAHLCitationSystematic reviewWeb of scienceInformation retrievalMEDLINETracking (education)Science Citation IndexData scienceComputer scienceCitation analysisMedicineMeta-analysisWorld Wide WebPsychologyPathologyBiology

Abstract

fetched live from OpenAlex

Background: Up-to-date guidance on comprehensive study identification for systematic reviews is crucial. According to current recommendations, systematic searching should combine electronic database searching with supplementary search methods. One such supplementary search method is citation tracking. It aims at collecting directly and/or indirectly cited and citing references from "seed references”. Tailored and evidence-guided recommendations concerning the use of citation tracking are strongly needed. Objective: We intend to develop recommendations for the use of citation tracking in health-related systematic literature searching. Our study will be guided by the following research questions: What are the benefits of citation tracking for health-related systematic literature searching? Which perspectives and experiences do experts in the field of literature retrieval methods have with regard to citation tracking in health-related systematic literature searching? Methods: Our study will have two parts: a scoping review and an expert survey. The scoping review aims at identifying methodological studies on benefits or problems of citation tracking in health-related systematic literature searching with no restrictions on study design, language, and publication date. We will perform database searching in MEDLINE, The Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science Core Collection, two information science databases, and free web searching. Two reviewers will independently assess full texts of selected abstracts. We will conduct direct backward and forward citation tracking on included articles. The results of the scoping review will inform our expert survey through which we aim to learn about experts΄ perspectives and experiences. We will narratively synthesize the results and derive recommendations for performing health-related systematic reviews.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.446
metaresearch head score (Gemma)0.588
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.554
Threshold uncertainty score0.683

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4460.588
Meta-epidemiology (narrow)0.0070.011
Meta-epidemiology (broad)0.0150.017
Bibliometrics0.0400.038
Science and technology studies0.0080.010
Scholarly communication0.0150.023
Open science0.0070.016
Research integrity0.0180.019
Insufficient payload (model declined to judge)0.1610.068

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.993
GPT teacher head0.823
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2020
Admission routes1
Has abstractyes

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