Edmonton Symptom Assessment System Screening and Depression at the End of Life
Bibliographic record
Abstract
data accrued from a randomized trial in which tamoxifen was given for two periods of time.There are three ways that one can examine data from a randomized trial, and in aggregate, we find these data to be less than compelling.First, the total proportion of women who experienced an adverse cardiovascular event was 18.5% in the 2-year tamoxifen arm and 17.5% in the 5-year arm (P ϭ .5).Second, the cumulative incidence curves for cardiovascular events in the 2-year arm and the 5-year arm (Fig A6 in the article by Haskshaw et al) are virtually overlapping.These results are hard to reconcile with the observation that among women age 50 to 59 years, the hazard ratio for cardiovascular events was 0.65 (95% CI, 0.47 to 0.88).The data for the younger women is represented graphically in Figure 4.It is odd that the separationinthetwocurvesseemstobewellunderwayatthe2-yearmark, yet both groups took an identical dose of tamoxifen up until this time.Given the discordant findings in the various analyses of this data, and the post hoc nature of the subgroup analysis, we think it is prudent to wait until all members of the cohort have had at least 10 years of follow-up before we can be confident of the interpretation of the results.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".