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Record W2753384065 · doi:10.1111/imr.12575

Host‐microbiota interactions and adaptive immunity

2017· review· en· W2753384065 on OpenAlex
Kathy D. McCoy, Francesca Ronchi, Markus B. Geuking

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImmunological Reviews · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of Calgary
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsBiologyAcquired immune systemImmune systemImmunityCompartmentalization (fire protection)ImmunologyInnate immune systemMucosal immunologyAntibody

Abstract

fetched live from OpenAlex

All mucosal surfaces are colonized with a vast number of microbes, which are essential for stimulating and regulating the immune system. While intrinsic and innate mechanisms exist to promote a strong barrier between the microbiota and the host to ensure compartmentalization, the microbiota is also able to induce robust adaptive immunity. In this review, we discuss the interplay between the microbiota and the adaptive immune system, with a focus on the induction of mucosal and systemic antibody responses and newly defined roles of maternal antibodies. We also highlight recent studies that aim to decipher microbial antigen-specificity of the T-cell compartment.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.013

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 head0.209
GPT teacher head0.394
Teacher spread0.186 · 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