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Record W2530827738 · doi:10.11613/bm.2016.035

IMPACT Observatory: tracking the evolution of clinical trial data sharing and research integrity

2016· review· en· W2530827738 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

VenueBiochemia Medica · 2016
Typereview
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversité de MontréalComputer Research Institute of Montréal
FundersFP7 People: Marie-Curie ActionsEuropean Commission
KeywordsData sharingClinical trialBusinessProcess (computing)Psychological interventionOpen dataData integrityMedicinePublic relationsPolitical scienceKnowledge managementComputer scienceComputer securityAlternative medicineNursingWorld Wide Web

Abstract

fetched live from OpenAlex

INTRODUCTION: The opening of research data is emerging thanks to the increasing possibilities of digital technology. The opening of clinical trial (CT) data is a part of this process, expected to have positive scientific, ethical, health, and economic impacts thus contributing to research integrity. The January 2016 proposal by the International Council of Medical Journal Editors triggered ample discussion about CT data sharing and reconfirmed the need for an ongoing assessment of its dynamics. The IMProving Access to Clinical Trials data (IMPACT) Observatory aims to play such a role, and assess the data sharing culture, policies, and practices of key players, the impact of their interventions on CTs, and contribute to a transformation of research. The objective of this paper is to present the IMPACT Observatory as well as share some of its preliminary findings. MATERIALS AND METHODS: Methods include a scoping study of research, surveys, interviews, and an environmental scan of research data repositories. RESULTS: Our preliminary findings indicate that although opening of CT data has not yet been achieved, its evolution is encouraging. Initiatives by key players contribute to increasing of CT data sharing, and many barriers are shrinking or disappearing. CONCLUSIONS: The major barrier is the lack of data sharing standards, from preparing data for public sharing to its curatorship, findability and access. However, experiences accumulated by sharing CT data according to "upon request" or "open" mechanisms could inform the development of such standards. The Vivli, CORBEL-ECRIN and Open Trials projects are currently working in this direction.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Reproducibility · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearchOpen scienceResearch integrity
Domain: Reproducibility · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.059
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science, Research integrity
Consensus categoriesMetaresearch, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0590.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.006
Open science0.0190.018
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.799
GPT teacher head0.630
Teacher spread0.169 · 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