Quality of abstracts of pilot trials in heart failure: A protocol for a systematic survey
Bibliographic record
Abstract
INTRODUCTION: Pilot trials are initial small-scale studies done to inform the design of larger trials. Their findings like other studies are usually disseminated as peer-reviewed journal articles. Abstracts are used to introduce the contents to readers, and give a general idea about the full reports and sometimes are the only source of information available to readers. Despite their importance, the contents of abstracts of trial reports are usually not informative enough and lack the essential details. METHODS AND ANALYSIS: This is a protocol for a planned systematic survey with a primary aim of analyzing the reporting quality measured as the completeness of the reporting of pilot trial abstracts in heart failure. The secondary aim will be to explore factors associated with better reporting quality.Abstracts of heart failure pilot trials in humans (journal and conference abstracts) published in the English language from 1 January 1990 to 30 November 2016 will be assessed to determine the reporting quality, based on the CONSORT 2010 statement extension to randomized pilot and feasibility trials. All non-pilot/feasibility trials and non-human pilot trials will be excluded. We will search Medline (PUBMED), Cochrane controlled trials register, Scopus and African wide information databases for pilot trials in heart failure. Title and abstracts of identified studies will be screened for inclusion and data extracted independently by two reviewers in duplicate without using the full text. Reported and unreported items on the abstracts will be presented as frequencies and percentages, a descriptive analysis will be used to interpret the reporting quality and regression analysis used for characteristics associated with greater statistical reporting at 95% confidence interval. REVIEW REGISTRATION NUMBER: PROSPERO CRD42016049911.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.385 | 0.372 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.041 | 0.018 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".