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Record W1986449731 · doi:10.4021/gr2009.04.1287

Bioinformatics Analysis and Validation of the Expressed Sequences Tag in Human Colorectal Adenocarcinoma

2009· article· en· W1986449731 on OpenAlexvenueno aff
Yao Chen

Bibliographic record

VenueGastroenterology Research · 2009
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsColorectal adenocarcinomaAdenocarcinomaSuppression subtractive hybridizationComplementary DNAMicroarrayColon adenocarcinomaMedicineMolecular biologyBioinformaticsComputational biologyGeneBiologyInternal medicinecDNA libraryGeneticsGene expressionCancer

Abstract

fetched live from OpenAlex

BACKGROUND: This study was to investigate some new pathological genes in colorectal adenocarcinoma of human. METHODS: Human colorectal adenocarcinoma tissues and normal colorectal tissues were taken and suppression subtractive hybridization (SSH) and cDNA microarray techniques were employed. From differentially expressed 86 expressed sequence tags (EST), 10 EST of the SSH were selected as seed sequence for bioinformatics analyses, semi-quantitative RT-PCR and PCR-sequencing. Each lane of semi-quantitative RT-PCR was analyzed by Q1 software. RESULTS: Among these 10 EST, it has been found that ES274070, ES274071, ES274076 and ES274081 may play role in the onset of colorectal adenocarcinoma in human. CONCLUSIONS: The ES274070, ES274071, ES274076 and ES274081 are related to the onset of human colorectal adenocarcinoma.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.353
Teacher spread0.311 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2009
Admission routes1
Has abstractyes

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