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Record W4254994248 · doi:10.1093/jnci/djj324

RESPONSE

2006· article· en· W4254994248 on OpenAlexaff
Dongsheng Tu, Joseph L. Pater, James N. Ingle, Paul E. Goss

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsKingston General HospitalOntario Institute for Cancer Research
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

We appreciate Dr Vakaet's compliments relating to our NCIC CTG MA17 clinical trial and would like to respond to the questions he raises regarding our updated report ( 1 ) . Vakaet notes the differences in the number of patients at risk and hence the number of breast cancer events between our first ( 2 ) and updated reports and raises the question as to whether the completeness of data follow-up should have been taken into consideration before the Data Safety and Monitoring Committee (DSMC) made the decision to terminate our study at the first planned interim analysis. He is correct that the main difference between these two reports is the completeness of follow-up and other data in the final analysis. However, the number of events reviewed by the DSMC at the interim analysis was sufficient to conclude that there was a substantial treatment effect, the statistical significance of which exceeded the preset stopping boundaries. Our final analysis further confirmed the decision made by the DSMC, a decision that we continue to stand by, and we do not agree that the trial was stopped prematurely. Vakaet also raises questions about the eligibility of some patients in our study and suggests that we report the distribution of the median time between initial diagnosis of breast cancer and random assignment to the trial as the 5th and 95th percentiles. As indicated in the first paragraph of the study population subsection of our JNCI article ( 1 ) , there were 14 patients who were ineligible because of too short or too long tamoxifen exposure but were included in the analysis based on an intent-to-treat principle. This explains the out-of-range values in the time between initial diagnosis of breast cancer and random assignment and in a more relevant variable, duration of tamoxifen therapy. We have calculated percentiles in these two variables as suggested: the 1st and 99th percentiles for the time between initial diagnosis of breast cancer and random assignment were, respectively, 56.5 and 80.2 months; the 1st and 99th percentiles for the more relevant variable, duration on tamoxifen, were, respectively, 4.5 and 5.9 years. The 5th and 95th percentiles were, respectively, 59.8 and 73.4 months for time between initial diagnosis of breast cancer and random assignment and 4.7 to 5.4 years for duration of tamoxifen.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.467
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.4670.231

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.

Opus teacher head0.012
GPT teacher head0.290
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractno

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