Bibliographic record
Abstract
Delay in diagnosis is a pejorative term for an interval better described as lag time, a period of considerable concern to health care administrators, providers, and consumers, receiving attention in numerous countries over many years. The general assumption that the longer the lag time the poorer the prospect for survival is not supported by the evidence that points to a more complex relationship. In some instances shorter lag times are associated with longer survival and in others correlate with shorter survival; in many instances there is no clear relationship. The associations between numerous demographic variables, such as the patient's age and the nature of the first health care contact, and lag time account for no more than 20% of the variance in this interval. It appears that more important determinants are the biology of the tumor and its related clinical behavior. Nevertheless, to minimize anxiety in patients and families, every effort should be made to reach a timely diagnosis. With the exceptions of retinoblastoma and malignant melanoma, campaigns to enhance public awareness have met with limited success with regard to reducing lag times in children and adolescents with cancer, indicating a challenge worthy of international attention.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads 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".