MétaCan
Menu
Back to cohort
Record W2613383989 · doi:10.1186/s41073-017-0031-1

Retractions in cancer research: a systematic survey

2017· article· en· W2613383989 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Integrity and Peer Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsJuravinski HospitalHamilton Health SciencesMcMaster University
Fundersnot available
KeywordsImpact factorMEDLINEMedicineDescriptive statisticsFamily medicineLibrary scienceComputer sciencePolitical scienceLawStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: The annual number of retracted publications in the scientific literature is rapidly increasing. The objective of this study was to determine the frequency and reason for retraction of cancer publications and to determine how journals in the cancer field handle retracted articles. METHODS: We searched three online databases (MEDLINE, Embase, The Cochrane Library) from database inception until 2015 for retracted journal publications related to cancer research. For each article, the reason for retraction was categorized as plagiarism, duplicate publication, fraud, error, authorship issues, or ethical issues. Accessibility of the retracted article was defined as intact, removed, or available but with a watermark over each page. Descriptive data was collected on each retracted article including number of citations, journal name and impact factor, study design, and time between publication and retraction. The publications were screened in duplicated and two reviewers extracted and categorized data. RESULTS: Following database search and article screening, we identified 571 retracted cancer publications. The majority (76.4%) of cancer retractions were issued in the most recent decade, with 16.6 and 6.7% of the retractions in the prior two decades respectively. Retractions were issued by journals with impact factors ranging from 0 (discontinued) to 55.8. The average impact factor was 5.4 (median 3.54, IQR 1.8-5.5). On average, a retracted article was cited 45 times (median 18, IQR 6-51), with a range of 0-742. Reasons for retraction include plagiarism (14.4%), fraud (28.4%), duplicate publication (18.2%), error (24.2%), authorship issues (3.9%), and ethical issues (2.1%). The reason for retraction was not stated in 9.8% of cases. Twenty-nine percent of retracted articles remain available online in their original form. CONCLUSIONS: Retractions in cancer research are increasing in frequency at a similar rate to all biomedical research retractions. Cancer retractions are largely due to academic misconduct. Consequences to cancer patients, the public at large, and the research community can be substantial and should be addressed with future research. Despite the implications of this important issue, some cancer journals currently fall short of the current guidelines for clearly stating the reason for retraction and identifying the publication as retracted.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.206
metaresearch head score (Gemma)0.182
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.480
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2060.182
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.012
Insufficient payload (model declined to judge)0.0010.000

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 head0.717
GPT teacher head0.631
Teacher spread0.087 · 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