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Record W2149823386 · doi:10.1158/1078-0432.ccr-06-1213

Advances in Treating Metastatic Bone Cancer: Summary Statement for the First Cambridge Conference

2006· article· en· W2149823386 on OpenAlexaff
Allan Lipton, James R. Berenson, Jean-Jacques Body, Brendan F. Boyce, Øyvind S. Bruland, Michael A. Carducci, Charles S. Cleeland, Denis R. Clohisy, Robert E. Coleman, Richard J. Cook, Theresa A. Guise, Roger Pearse, Trevor J. Powles, Michael J. Rogers, G. David Roodman, Matthew R. Smith, Larry J. Suva, Robert L. Vessella, Katherine N. Weilbaecher, Laura King

Bibliographic record

VenueClinical Cancer Research · 2006
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsUniversity of Waterloo
FundersNational Cancer Institute
KeywordsStatement (logic)MedicineBone cancerCancerMultiple myelomaNatural historyLibrary scienceInternal medicineComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The First Cambridge Conference on Advances in Treating Metastatic Bone Cancer, a symposium held in Cambridge, Massachusetts, October 28 to 29, 2005, was convened to discuss recent advances and research related to the natural history of bone metastases and skeletal complications, bone cancer biology, treatment of myeloma and other solid tumors, and treatment-induced bone loss. The conference format combined brief presentations with extended periods of discussion. The conclusions reached during the 2-day meeting are summarized in this article and presented in more detail in the individual articles and accompanying discussion sessions that comprise the conference proceedings.

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)0.005
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: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0170.007

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 head0.299
GPT teacher head0.578
Teacher spread0.279 · 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
GenreReview

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

Citations30
Published2006
Admission routes1
Has abstractyes

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