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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 OpenAlexaboutno aff
Matthew M. Gubin

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.

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)0.007
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0500.018

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

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
GenreOther

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

Citations3
Published2017
Admission routes1
Has abstractyes

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