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Record W4394410644 · doi:10.6084/m9.figshare.20003709

Additional file 1 of A stratification model of hepatocellular carcinoma based on expression profiles of cells in the tumor microenvironment

2022· dataset· en· W4394410644 on OpenAlexaff
Chunting Zeng, Linmeng Zhang, Chanhua Luo, Chen Yang, Xiaowen Huang, Linfeng Fan, Jiarong Li, Fengsheng Chen, Zelong Luo

Bibliographic record

VenueOpen MIND · 2022
Typedataset
Languageen
FieldMathematics
TopicMathematical Biology Tumor Growth
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsHepatocellular carcinomaStratification (seeds)Risk stratificationTumor microenvironmentExpression (computer science)Cancer researchBiologyTumor cellsOncologyInternal medicineComputer scienceMedicine

Abstract

fetched live from OpenAlex

Additional file 1: Table S1. Results of the Kyoto Encyclopedia of Genes and Genomes enrichment analysis

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 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 score0.851
Threshold uncertainty score0.624

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.8510.000

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 head0.056
GPT teacher head0.274
Teacher spread0.218 · 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
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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Same venueOpen MINDSame topicMathematical Biology Tumor GrowthFrench-language works237,207