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Record W1974488253 · doi:10.1016/j.bbmt.2007.08.005

Blood and Marrow Transplant Clinical Trials Network State of the Science Symposium 2007

2007· article· en· W1974488253 on OpenAlexaff
James L.M. Ferrara, Claudio Anasetti, Edward A. Stadtmauer, Joseph H. Antin, John R. Wingard, Stephanie J. Lee, John E. Levine, Kirk R. Schultz, Frederick R. Appelbaum, Robert S. Negrin, Sergio Giralt, Christopher Bredeson, Helen E. Heslop, Mary Horowitz

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2007
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity of British Columbia
FundersNational Heart, Lung, and Blood InstituteNational Cancer InstituteU.S. Department of Health and Human ServicesNational Institutes of HealthAmerican Cancer SocietyLeukemia and Lymphoma Society
KeywordsMedicineClinical trialHematopoietic cellHematopoietic stem cell transplantationBone transplantationHaematopoiesisStem cellHematopoietic stem cellTransplantationBone marrow transplantIntensive care medicineOncologyInternal medicineBone marrow transplantationSurgery

Abstract

fetched live from OpenAlex

Outcomes of hematopoietic cell transplantation are steadily improving. New techniques have reduced transplant toxicities, and there are new sources of hematopoietic stem cells from unrelated donors. In June 2007 the Blood and Marrow Transplant Clinical Trials Network convened a State of the Science Symposium of more than 200 participants in Ann Arbor to identify the most compelling clinical research opportunities in the field. This report summarizes the symposium's discussions and identifies eleven high priority clinical trials that the network plans to pursue over the course of the next several years.

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)0.016
metaresearch head score (Gemma)0.009
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: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0070.002
Open science0.0010.001
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0310.013

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 head0.037
GPT teacher head0.337
Teacher spread0.300 · 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
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

Citations35
Published2007
Admission routes1
Has abstractno

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