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Record W1963863438 · doi:10.1038/bjc.2016.441

Erratum: Galectin-1 has potential prognostic significance and is implicated in clear cell renal cell carcinoma progression through the HIF/mTOR signaling axis

2017· erratum· en· W1963863438 on OpenAlexaff
Nicole M. White, Olena Masui, Daniel Newsted, Andreas Scorilas, Alexander D. Romaschin, Georg A. Bjarnason, K. W. Michael Siu, George M. Yousef

Bibliographic record

VenueBritish Journal of Cancer · 2017
Typeerratum
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoYork UniversitySt. Michael's Hospital
Fundersnot available
KeywordsCancer researchPI3K/AKT/mTOR pathwayClear cell renal cell carcinomaProtein kinase BBiologyRenal cell carcinomaGalectin-1MetastasisImmunohistochemistryTargeted therapyGalectin-3P70-S6 Kinase 1Signal transductionCancerMedicinePathologyInternal medicineImmunologyCell biology

Abstract

fetched live from OpenAlex

Correction to: British Journal of Cancer (2014) 110, 1250–1259; doi:10.1038/bjc.2013.828; Published online 4 February 2014 The authors of this paper would like to add the following statement to the acknowledgements section: We thank Mr Andrew Girgis for his role in the analysis of the TCGA data.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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

Citations52
Published2017
Admission routes1
Has abstractyes

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