Does knowledge have a half-life? An observational study analyzing the use of older citations in medical and scientific publications
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.
Bibliographic record
Abstract
OBJECTIVES: In the process of scientific progress, prior evidence is both relied on and supplanted by new discoveries. We use the term 'knowledge half-life' to refer to the phenomenon in which older knowledge is discounted in favour of newer research. By quantifying the knowledge half-life, we sought to determine whether research published in more recent years is preferentially cited over older research in medical and scientific articles. DESIGN: An observational study employing a directed, systematic search of current literature. DATA SOURCES: were searched. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Eight high-impact medical and scientific journals were sampled examining original research articles from the first issue of every year over a 25-year span (1996-2020). The outcome of interest was the difference between the publication year of the article and references cited, termed 'citation lag'. DATA EXTRACTION AND SYNTHESIS: Analysis of variance was used to identify significant differences in citation lag. RESULTS: A total of 726 articles and 17 895 references were included with a mean citation lag of 7.5±8.4 years. Across all journals, >70% of references had been published within 10 years of the citing article. Approximately 15%-20% of referenced articles were 10-19 years old, and articles more than 20 years old were cited infrequently. Medical journals articles had references with significantly shorter citation lags compared with general science journals (p≤0.01). Articles published before 2009 had references with significantly shorter citation lags compared with those published in 2010-2020 (p<0.001). CONCLUSIONS: This study found evidence of a small increase in the citation of older research in medical and scientific literature over the past decade. This phenomenon deserves further characterisation and scrutiny to ensure that 'old knowledge' is not being lost.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it