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Record W2151073109 · doi:10.1002/path.4632

Cross‐species models of human melanoma

2015· review· en· W2151073109 on OpenAlex
Louise van der Weyden, E. Elizabeth Patton, Geoffrey A. Wood, Alastair K. Foote, Thomas Brenn, Mark J. Arends, David J. Adams

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Pathology · 2015
Typereview
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsUniversity of Guelph
FundersWellcomeMedical Research CouncilMedical Research Council CanadaEuropean Research CouncilCancer Research UKWellcome Trust
KeywordsMelanomaBiologyCancer research

Abstract

fetched live from OpenAlex

Although transformation of melanocytes to melanoma is rare, the rapid growth, systemic spread, as well as the chemoresistance of melanoma present significant challenges for patient care. Here we review animal models of melanoma, including murine, canine, equine, and zebrafish models, and detail the immense contribution these models have made to our knowledge of human melanoma development, and to melanocyte biology. We also highlight the opportunities for cross‐species comparative genomic studies of melanoma to identify the key molecular events that drive this complex disease. © 2015 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.119
GPT teacher head0.380
Teacher spread0.261 · 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