Clinical reporting for personalized cancer genomics requires extensive access to subscription-only literature
Bibliographic record
Abstract
Objective: Medical care for cancer is increasingly directed by genomic laboratory testing for alterations in the tumor genome that are significant for diagnosis, prognosis and therapy. Uniquely in medicine, providers must search the biomedical literature for each patient to determine the clinical significance of these alterations. Access to published scientific literature is frequently subject to high fees, with access limited to institutional subscriptions. We sought to investigate the degree to which the scientific literature is accessible to clinical cancer genomics providers, and the potential role of university and hospital system libraries in information access for cancer care. Methods: We identified 265 journals that were accessed during the interpretation and reporting of clinical test results from 1,842 cancer patients at the University Health Network (Toronto, Canada). We determined the degree of open access for this set of clinically important literature, and for any journals not available through open access we surveyed subscription access at seven academic hospital systems and at their affiliated universities. Results: This study found that nearly half (116/265) of journals have open access mandates that make articles freely available within one year of release. For the remaining subscription access journals, universities provided a uniformly high level of access, but access available through hospital system collections varied widely. Conclusion: This study highlights the importance of different modes of access to the use of the scientific literature in clinical practice and points to challenges that must be overcome as genomic medicine grows in scale and complexity.
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How this classification was reachedexpand
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".