Bibliographic record
Abstract
DNA microarrays can measure the gene expression of thousands of genes at a time to identify differentially expressed genes. The Affymetrix GeneChip system is a platform for the high-density oligonucleotide microarray to measure gene expression using hundreds of thousands of 25-mer oligonucleotide probes. To deal with Affymetrix microarray data, there are three stages of preprocessing to produce gene expression measurements/values. These are background correction, normalization and summarization. At each stage, numerous methods have been developed. Our study is based on Affymetrix MG_U74Av2 chip with 12488 probe sets. Two strains of mice called NOR and NOR.NOD_Idd4/11 mouse are hybridized for the experiment. We apply a number of commonly used and state-of-art normalization methods to the data set, thus compute the expression measurements for different methods. The major methods we discuss include Robust Multi-chip Average (RMA), MAS 5.0, GCRMA, PLIER and dChip. Comparisons in terms of correlation coefficient, pairwise expression measures plot, fold change and Significance Analysis of Microarray (SAM) are conducted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".