Oligonucleotide Array Comparative Genomic Hybridization (oaCGH) based characterization of genetic deficiencies as an aid to gene mapping in Caenorhabditis elegans
Bibliographic record
Abstract
BACKGROUND: A collection of genetic deficiencies covering over 70% of the Caenorhabditis elegans genome exists, however the application of these valuable biological tools has been limited due to the incomplete correlation between their genetic and physical characterization. RESULTS: We have applied oligonucleotide array Comparative Genomic Hybridization (oaCGH) to the high resolution, molecular characterization of several genetic deficiency and duplication strains in a 5 Mb region of Chromosome III. We incorporate this data into a physical deficiency map which is subsequently used to direct the positional cloning of essential genes within the region. From this analysis we are able to quickly determine the molecular identity of several previously unidentified mutations. CONCLUSION: We have applied accurate, high resolution molecular analysis to the characterization of genetic mapping tools in Caenorhabditis elegans. Consequently we have generated a valuable physical mapping resource, which we have demonstrated can aid in the rapid molecular identification of mutations of interest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".