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Record W2770117570 · doi:10.1148/radiol.2017170586

Are Study and Journal Characteristics Reliable Indicators of “Truth” in Imaging Research?

2017· review· en· W2770117570 on OpenAlexaff
Robert Frank, Matthew D. F. McInnes, Deborah Levine, Herbert Y. Kressel, Julia S Jesurum, William Petrcich, Trevor A. McGrath, Patrick M. Bossuyt

Bibliographic record

VenueRadiology · 2017
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineMeta-analysisConfidence intervalStandard deviationMean differenceStatisticsPublication biasPooled varianceMEDLINENuclear medicineInternal medicineMathematics

Abstract

fetched live from OpenAlex

Purpose To evaluate whether journal-level variables (impact factor, cited half-life, and Standards for Reporting of Diagnostic Accuracy Studies [STARD] endorsement) and study-level variables (citation rate, timing of publication, and order of publication) are associated with the distance between primary study results and summary estimates from meta-analyses. Materials and Methods MEDLINE was searched for meta-analyses of imaging diagnostic accuracy studies, published from January 2005 to April 2016. Data on journal-level and primary-study variables were extracted for each meta-analysis. Primary studies were dichotomized by variable as first versus subsequent publication, publication before versus after STARD introduction, STARD endorsement, or by median split. The mean absolute deviation of primary study estimates from the corresponding summary estimates for sensitivity and specificity was compared between groups. Means and confidence intervals were obtained by using bootstrap resampling; P values were calculated by using a t test. Results Ninety-eight meta-analyses summarizing 1458 primary studies met the inclusion criteria. There was substantial variability, but no significant differences, in deviations from the summary estimate between paired groups (P > .0041 in all comparisons). The largest difference found was in mean deviation for sensitivity, which was observed for publication timing, where studies published first on a topic demonstrated a mean deviation that was 2.5 percentage points smaller than subsequently published studies (P = .005). For journal-level factors, the greatest difference found (1.8 percentage points; P = .088) was in mean deviation for sensitivity in journals with impact factors above the median compared with those below the median. Conclusion Journal- and study-level variables considered important when evaluating diagnostic accuracy information to guide clinical decisions are not systematically associated with distance from the truth; critical appraisal of individual articles is recommended. © RSNA, 2017 Online supplemental material is available for this article.

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)0.390
metaresearch head score (Gemma)0.743
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.610
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3900.743
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0100.015
Bibliometrics0.0130.022
Science and technology studies0.0020.007
Scholarly communication0.0100.010
Open science0.0050.005
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.900
GPT teacher head0.660
Teacher spread0.240 · 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 designSystematic review
DomainEvaluation
GenreReview

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

Citations14
Published2017
Admission routes1
Has abstractyes

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