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Record W4211179856 · doi:10.4161/onci.22789

Trial watch

2012· article· en· W4211179856 on OpenAlex
Erika Vacchelli, Alexander Eggermont, Jérôme Galon, Catherine Sautès‐Fridman, Laurence Zitvogel, Guido Kroemer, Lorenzo Galluzzi

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.

fundA Canadian funder is recorded on the work.
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

VenueOncoImmunology · 2012
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsnot available
FundersInstitute of Cancer ResearchInstitut National Du Cancer
KeywordsClinical trialMedicineMonoclonal antibodyCancerBasic researchCancer researchAntibodyImmunologyPathologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

During the past 20 years, dozens—if not hundreds—of monoclonal antibodies have been developed and characterized for their capacity to mediate antineoplastic effects, either as they activate/enhance tumor-specific immune responses, either as they interrupt cancer cell-intrinsic signal transduction cascades, either as they specifically delivery toxins to malignant cells or as they block the tumor-stroma interaction. Such an intense research effort has lead to the approval by FDA of no less than 14 distinct molecules for use in humans affected by hematological or solid malignancies. In the inaugural issue of OncoImmunology, we briefly described the scientific rationale behind the use of monoclonal antibodies in cancer therapy and discussed recent, ongoing clinical studies investigating the safety and efficacy of this approach in patients. Here, we summarize the latest developments in this exciting area of clinical research, focusing on high impact studies that have been published during the last 15 months and clinical trials launched in the same period to investigate the therapeutic profile of promising, yet hitherto investigational, monoclonal antibodies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.999

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)0.0020.002

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 head0.051
GPT teacher head0.374
Teacher spread0.322 · 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