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Record W2792540082 · doi:10.1080/2162402x.2018.1442169

Heating it up: Oncolytic viruses make tumors ‘hot’ and suitable for checkpoint blockade immunotherapies

2018· editorial· en· W2792540082 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOncoImmunology · 2018
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
FundersLabex Immuno-OncologyEuropean Research Area Network on Cardiovascular DiseasesLigue Contre le CancerFondation pour la Recherche MédicaleInstitut National Du CancerInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la RechercheGovernment of CanadaCanadian Institutes of Health ResearchAssociation pour la Recherche sur le CancerSeerave FoundationInstitut Universitaire de FranceBeatrice Hunter Cancer Research InstituteFondation LeducqEuropean Commission
KeywordsOncolytic virusBlockadeImmune checkpointTumor microenvironmentMedicineImmunotherapyAdjuvantCancer researchImmune systemImmunologyReceptorInternal medicine

Abstract

fetched live from OpenAlex

Immune checkpoint blockade is less efficient in patients bearing immunologically ‘cold’ tumors. Oncolytic viruses, which were originally discovered for their ability to preferentially kill malignant cells, can recondition the tumor microenvironment. Supporting this hypothesis, two new studies published in Science Translational Medicine show that adjuvant-like activities of oncolytic viruses make brain and breast tumors ‘hot’ and sensitize them for subsequent immune checkpoint blockade.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.021
GPT teacher head0.329
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