Quality of Abstracts in the Context of a Systematic Review on Parenting of Children with Chronic Health Conditions and Disabilities
Bibliographic record
Abstract
In this study the authors address the quality of abstracts reviewed during a systematic review. Their objective was to describe the proportion of abstracts that could not be coded and to explore factors associated with that outcome. Using an exploratory design, a database of titles uploaded for analysis was examined for clarity, type and year of publication, and abstract format. Of the 1851 references examined, 481 (26%) were coded as unclear. The inter-rater reliability Kappa score was 0.777. These abstracts were more likely to have been published prior to 2002 and did not use a structured format. Abstracts are an important tool in the systematic review process. Structured abstracts can reduce the time and costs associated with conducting a systematic review.
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 | 0.478 | 0.855 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.051 | 0.057 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".