MétaCan
Menu
Back to cohort
Record W1602732985 · doi:10.1080/2162402x.2015.1026529

Survivin-targeted immunotherapy drives robust polyfunctional T cell generation and differentiation in advanced ovarian cancer patients

2015· article· en· W1602732985 on OpenAlex
Neil L. Berinstein, Mohan Karkada, Amit M. Oza, Kunle Odunsi, Jeannine Villella, John Nemunaitis, Michael A. Morse, Tanja Pejović, J. Bentley, Marc Buyse, Rita Nigam, Genevieve Weir, Lisa D. MacDonald, Tara Quinton, Rajkannan Rajagopalan, Kendall Sharp, Andrea Penwell, Leeladhar Sammatur, Tomasz Burzykowski, Marianne M. Stanford, Marc Mansour

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

VenueOncoImmunology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsNova Scotia Health AuthorityPrincess Margaret Cancer CentreUniversity Health NetworkImmunovaccine (Canada)Health Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsImmune systemCD8SurvivinImmunotherapyAntigenImmunologyMedicineCancer researchCytotoxic T cellOvarian cancerCancer immunotherapyT cellTumor antigenCancerBiologyInternal medicine

Abstract

fetched live from OpenAlex

T cells and provided a strong rationale for further testing to determine clinical benefits associated with this immune activation. These data represent vaccine-induced T cell activation in a clinical setting to a self-tumor antigen previously described only in animal models.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.235
Teacher spread0.218 · 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