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Record W2621331192 · doi:10.1158/2326-6066.cir-17-0224

Cancer Immunology and Immunotherapy: Taking a Place in Mainstream Oncology Keystone Symposia Meeting Summary

2017· article· en· W2621331192 on OpenAlex
Matthew M. Gubin

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueCancer Immunology Research · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
FundersNovartis Institutes for BioMedical ResearchCalifornia Institute of TechnologyUniversity of California, San FranciscoMemorial Sloan-Kettering Cancer CenterUniversity of California, San DiegoNational Cancer InstituteNational Institutes of HealthCancer Research Institute
KeywordsTumor immunologyImmunotherapyMedicineCancer immunotherapyMainstreamCancerCancer immunologyClinical OncologyImmunologyOncologyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

Abstract The Keystone Symposia conference on Cancer Immunology and Immunotherapy: Taking a Place in Mainstream Oncology was held at the Fairmont Chateau in Whistler, British Columbia, Canada, on March 19–23, 2017. The conference brought together a sold-out audience of 654 scientists, clinicians, and others from both academia and industry to discuss the latest developments in cancer immunology and immunotherapy. This meeting report summarizes the main themes that emerged during the four-day conference. Cancer Immunol Res; 5(6); 434–8. ©2017 AACR.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.066
GPT teacher head0.421
Teacher spread0.354 · 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