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Record W4403303574 · doi:10.1111/pcmr.13205

Meeting Report From the 2023 Cure Ocular Melanoma (<scp>CURE OM</scp>) Global Science Meeting, Philadelphia, <scp>PA</scp>, November 2023

2024· article· en· W4403303574 on OpenAlexaff
Rino S. Seedor, Andrew E. Aplin, Corine Bertolotto, Richard D. Carvajal, Nigel Deacon, Katie Doble, Omid Hamid, Rizwan Haq, Miriam Kadosh, Shaheer Khan, Jacqueline Kraska, Jose Lutzky, Meredith McKean, Kamaneh Montazeri, Justin C. Moser, Michael D. Onken, Marlana Orloff, Joseph J. Sacco, Keiran S.M. Smalley, Sara Selig

Bibliographic record

VenuePigment Cell & Melanoma Research · 2024
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsCanadian Patient Safety Institute
FundersEMD SeronoGenentechPlexxikonAstellas PharmaEisaiCastle BiosciencesG1 TherapeuticsAscentage PharmaPfizerModernaIncyteBeiGeneMelanoma Research FoundationGlaxoSmithKlineTizona TherapeuticsAstraZenecaNovocureMereo BioPharmaCelldex TherapeuticsDaiichi Sankyo EuropeFoghorn TherapeuticsGilead SciencesRegeneron PharmaceuticalsMelanoma Research AllianceBristol-Myers SquibbAmerican Society of Clinical OncologyAmgenNGM BiopharmaceuticalsExelixisSanofi
KeywordsMedicineMelanomaGerontologyCancer research

Abstract

fetched live from OpenAlex

The 2023 Cure Ocular Melanoma (CURE OM) Global Science Meeting was held in Philadelphia on November 6, 2023. There is increased awareness and dedicated research in uveal melanoma (UM), but unmet needs remain in the prevention, detection, and treatment of UM. The purpose of this meeting was to provide an international forum for the exchange of research ideas, to allow for discussion of basic science as well as clinical research on UM, and to gather input about advocacy and patient needs.

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 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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.003

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 head0.041
GPT teacher head0.359
Teacher spread0.318 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

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