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Record W2164162533 · doi:10.1093/jnci/92.9.671a

MEMORANDUM FOR: Science Writers and Editors on the Journal Press List

2000· article· en· W2164162533 on OpenAlexaboutno aff
Katherine Arnold, Dan Eckstein

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2000
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsnot available
Fundersnot available
KeywordsMemorandumLibrary sciencePolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

April 27, 2000 (EMBARGOED FOR RELEASE 4 P.M. EDT May 2) A combination of paclitaxel and cisplatin is the new “gold standard” for treating advanced ovarian cancer, according to the authors of a randomized trial comparing this combination with cyclophosphamide and cisplatin. Martine Piccart, M.D., of the European Organization for Research and Treatment of Cancer (EORTC), with coauthors from the Nordic Gynecological Cancer Study Group (NOCOVA), the National Cancer Institute of Canada Clinical Trials Group (NCI-C-CTG), and the Scottish Group, present the results of their unique trans-Atlantic clinical study in the May 3 issue of the Journal of the National Cancer Institute. An earlier trial conducted by the Gynecologic Oncology Group in the United States showed a better outcome for patients with advanced ovarian cancer on the paclitaxel–cisplatin regimen than for those on a standard cyclophosphamide–cisplatin regimen. The European and Canadian investigators conducted a confirmatory trial that included somewhat broader selection criteria than the earlier trial and administered paclitaxel as a 3-hour instead of a 24-hour infusion.

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)0.006
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0080.003
Open science0.0030.002
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.1500.163

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 head0.184
GPT teacher head0.447
Teacher spread0.263 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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