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Record W4394234453 · doi:10.6084/m9.figshare.19234573

Additional file 2 of Predictive role of ferroptosis-related long non-coding RNAs in bladder cancer and their association with immune microenvironment and immunotherapy response

2022· dataset· en· W4394234453 on OpenAlexaff
Jingchao Liu, Zhipeng Zhang, Xiaodong Liu, Wei Zhang, Lingfeng Meng, Jiawen Wang, Zhengtong Lv, Haoran Xia, Yaoguang Zhang, Jianye Wang

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsBruyère
Fundersnot available
KeywordsImmunotherapyImmune systemBladder cancerTumor microenvironmentCoding (social sciences)Cancer immunotherapyLong non-coding RNACancerImmunologyBiologyMedicineCancer researchInternal medicineGeneticsRNAGeneSociology

Abstract

fetched live from OpenAlex

Additional file 2: Table S1. The expression matrix of TCGA cohort. Table S2. The downloaded clinical files of TCGA cohort. Table S3. The expression matrix of GEO cohort. Table S4. The downloaded clinical files of GEO cohort. Table S5. The Genome Reference file discriminating lncRNAs and mRNAs. Table S6. The expression matrix of lncRNAs during TCGA cohort. Table S7. The expression matrix of mRNAs during TCGA cohort. Table S8. The expression matrix of lncRNAs during GEO cohort. Table S9. The expression matrix of mRNAs during GEO cohort. Table S10. The detailed list of ferroptosis-related genes. Table S11. The expression matrix of ferroptosis-related genes during TCGA cohort. Table S12. The co-expression analysis results between lncRNAs and mRNAs. Table S13. The expression matrix of ferroptosis lncRNAs. Table S14. Detailed list of 59 differentially expressed ferroptosis genes between bladder cancer and normal tissues. Table S15. Detailed list of 538 differentially expressed ferroptosis lncRNAs between bladder cancer and normal tissues. Table S16. Detailed expression matrix of differentially expressed ferroptosis genes between bladder cancer and normal tissues. Table S17. Detailed expression matrix of differentially expressed ferroptosis lncRNAs between bladder cancer and normal tissues. Table S18. The merged document including both ferroptosis lncRNA expression and clinical information. Table S19. Detailed expression matrix of prognostic ferroptosis lncRNAs. Table S20. Detailed ferroptosis lncRNAs included in risk signature. Table S21. Detailed risk results depending on lncRNA risk signature in TCGA cohort. Table S22. Detailed risk results depending on lncRNA risk signature in GEO cohort. Table S23. The significantly enriched biological activities during high risk group. Table S24. The significantly enriched biological activities during low risk group. Table 25. The infiltration levels of various immune cells from http://timer.comp-genomics.org . Table S26. The detailed list of immune checkpoints-related genes. Table S27. The immunotherapy scoring information for TCGA cohort.

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)0.002
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.791
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.7910.094

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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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