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Record W2418788752 · doi:10.1007/978-1-59745-396-7

Macrophages and Dendritic Cells

2009· book· en· W2418788752 on OpenAlexfundno aff
Neil E. Reiner

Bibliographic record

VenueMethods in molecular biology · 2009
Typebook
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
FundersDepartment of Medicine, University of TorontoRoy J. and Lucille A. Carver College of Medicine, University of IowaU.S. Department of Veterans AffairsUniversity of TorontoUniversity of Colorado DenverUniversity of Cape TownHospital for Sick ChildrenUniversity of PennsylvaniaAgency for Science, Technology and ResearchUniversità degli Studi di Milano-BicoccaCollege of Veterinary Medicine, Cornell UniversityChang Gung UniversityKarolinska InstitutetInstitut National de la Santé et de la Recherche MédicaleCentre National de la Recherche ScientifiqueVrije Universiteit AmsterdamWeizmann Institute of ScienceUniversity of OxfordChang Gung Medical FoundationImperial College LondonTU Graz, Internationale Beziehungen und MobilitätsprogrammeUniversity Health NetworkVancouver Coastal Health Research InstituteToronto General Hospital Research Institute, University Health NetworkUniversitat de BarcelonaInstitute for Research in Biomedicine
KeywordsCell biologyBiology

Abstract

fetched live from OpenAlex

In light of the critical contributions of macrophages and dendritic cells to diverse inflammatory diseases and to immunity and host defense, state-of-the-art approaches to the investigation of their b

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.335
Teacher spread0.322 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations49
Published2009
Admission routes1
Has abstractyes

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