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Record W2430573464 · doi:10.1186/s40425-016-0142-0

Society for immunotherapy of cancer (SITC) statement on the proposed changes to the common rule

2016· article· en· W2430573464 on OpenAlexaff
Howard L. Kaufman, Lisa H. Butterfield, Pierre G. Coulie, Sandra Demaria, Robert L. Ferris, Jérôme Galon, Samir N. Khleif, Ira Mellman, Pamela S. Ohashi, Willem W. Overwijk, Suzanne L. Topalian, Francesco M. Marincola

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsClinical trialCommon RuleMedicineGovernment (linguistics)DeclarationCancer immunotherapyStandardizationCancerImmunotherapyAlternative medicineEngineering ethicsInformed consentPolitical sciencePathologyLawInternal medicine

Abstract

fetched live from OpenAlex

The Common Rule is a set of ethical principles that provide guidance on the management of human subjects taking part in biomedical and behavioral research in the United States. The elements of the Common Rule were initially developed in 1981 following a revision of the Declaration of Helsinki in 1975. Most academic facilities follow the Common Rule in the regulation of clinical trials research. Recently, the government has suggested a revision of the Common Rule to include more contemporary and streamlined oversight of clinical research. In this commentary, the leadership of the Society for Immunotherapy of Cancer (SITC) provides their opinion on this plan. While the Society recognizes the considerable contribution of clinical research in supporting progress in tumor immunotherapy and supports the need for revisions to the Common Rule, there is also some concern over certain elements which may restrict access to biospecimens and clinical data at a time when high throughput technologies, computational biology and assay standardization is allowing major advances in understanding cancer biology and providing potential predictive biomarkers of immunotherapy response. The Society values its professional commitment to patients for improving clinical outcomes with tumor immunotherapy and supports continued discussion with all stakeholders before implementing changes to the Common Rule in order to ensure maximal patient protections while promoting continued clinical research at this historic time in cancer research.

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)0.091
metaresearch head score (Gemma)0.167
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.121
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.167
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.008
Bibliometrics0.0020.002
Science and technology studies0.0080.016
Scholarly communication0.0160.008
Open science0.0100.010
Research integrity0.1210.125
Insufficient payload (model declined to judge)0.0050.007

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 head0.036
GPT teacher head0.362
Teacher spread0.327 · 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
GenreCommentary

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

Citations1
Published2016
Admission routes1
Has abstractyes

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