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Record W3017272456 · doi:10.1126/sciimmunol.aav3942

IFN-III is selectively produced by cDC1 and predicts good clinical outcome in breast cancer

2020· article· en· W3017272456 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScience Immunology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
FundersCentre Léon BérardInstitut national de la recherche scientifiqueRégion Auvergne-Rhône-AlpesLigue Contre le CancerLabEx DEvweCANFondation ARC pour la Recherche sur le CancerAgence Nationale de la RechercheEuropean Research CouncilAgence Nationale de Recherches sur le Sida et les Hépatites ViralesEuropean Society for Medical OncologyInstitut National Du CancerInstitut National de la Santé et de la Recherche MédicaleUniversité Claude Bernard Lyon 1Université de Lyon
KeywordsImmune systemImmunotherapyCancer researchChemokineTumor microenvironmentDendritic cellCCR4BiologyInterferonImmunologyCytotoxic T cellMedicineChemokine receptor

Abstract

fetched live from OpenAlex

1 microenvironment through increased production of IL-12p70, IFN-γ, and cytotoxic lymphocyte-recruiting chemokines. Last, we showed that engagement of TLR3 is a therapeutic strategy to induce IFN-III production by tumor-associated cDC1. These data provide insight into potential IFN- or cDC1-targeting antitumor therapies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.320
Teacher spread0.294 · 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