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Record W4206512154 · doi:10.1002/cti2.1363

Comparison of the tumor microenvironments of squamous cell carcinoma at different anatomical locations within the upper aerodigestive tract in relation to response to ICI therapy

2022· review· en· W4206512154 on OpenAlexaff
Maurice van Duijvenvoorde, Sarah Derks, Idris Bahce, C. René Leemans, Rieneke van de Ven, Marieke F. Fransen

Bibliographic record

VenueClinical & Translational Immunology · 2022
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsImmunotherapyTumor microenvironmentHead and neck squamous-cell carcinomaMedicineCancerImmune systemEsophagusBasal cellCarcinomaLung cancerHead and neck cancerCancer researchPathologyOncologyInternal medicineImmunology

Abstract

fetched live from OpenAlex

Immunotherapy with immune checkpoint inhibitors (ICI) has improved treatment outcomes in many cancer types and has focused attention on cancer immunity and the role of the tumor microenvironment (TME). Studies into efficacy of immunotherapy and TME are generally restricted to tumors in one anatomical location, while the histological type may have substantial influence on the contexture of the TME, perhaps more so than anatomical location, and subsequently to the response to immunotherapy. This review aims to focus on the TME in ICI-treated tumors of the same histological type, namely carcinogen-induced squamous cell carcinoma developing within the aerodigestive tract, at three locations, i.e. head and neck (HNSCC), esophagus (ESCC) and lung (LUSC).

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.092
GPT teacher head0.400
Teacher spread0.308 · 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
GenreReview

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

Citations9
Published2022
Admission routes1
Has abstractyes

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