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Record W2163030440 · doi:10.1016/j.bbmt.2011.06.007

NCI, NHLBI First International Consensus Conference on Late Effects after Pediatric Hematopoietic Cell Transplantation: State of the Science, Future Directions

2011· editorial· en· W2163030440 on OpenAlexaff
K. Scott Baker, Ravi Bhatia, Nancy Bunin, Michael L. Nieder, Christopher C. Dvorak, Lillian Sung, Jean E. Sanders, Joanne Kurtzberg, Michael A. Pulsipher

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2011
Typeeditorial
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick Children
FundersNational Heart, Lung, and Blood InstituteOtsuka PharmaceuticalOtsuka America PharmaceuticalOtsuka AmericaSt. Baldrick's FoundationLance Armstrong FoundationSigma-Tau PharmaceuticalsNational Cancer InstituteU.S. Department of Health and Human Services
KeywordsMedicineConsensus conferenceTransplantationHematopoietic cellState (computer science)Field (mathematics)Survivorship curveSet (abstract data type)Engineering ethicsHaematopoiesisStem cellComputer scienceSurgeryEngineeringEnvironmental health

Abstract

fetched live from OpenAlex

On April 28-29, 2011, a conference titled, “Late Effects after Pediatric Hematopoietic Cell Transplantation: State of the Science, Future Directions” was held in Arlington, VA, with a goal of bringing together leaders in the field of pediatric transplantation survivorship to review the current state of knowledge and define gaps in the field, develop consensus on critical areas for future research, and determine the best study designs to effectively address these questions. Over the course of the next several months, 6 summary articles covering the major topics discussed at the conference will be published in this journal, which will define and set forth recommendations for a research agenda to move this field forward over the next decade.

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)0.034
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.034
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0070.004
Open science0.0030.001
Research integrity0.0150.025
Insufficient payload (model declined to judge)0.0040.004

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.

Opus teacher head0.009
GPT teacher head0.249
Teacher spread0.240 · 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
GenreEditorial

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

Citations19
Published2011
Admission routes1
Has abstractyes

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