Production of Haploid and Diploid Androgenetic Zebrafish
Bibliographic record
Abstract
Zebrafish ( Danio rerio ) are a popular vertebrate model system, particularly useful for research in developmental genetics and neurobiology. The adults are easy to obtain and rear; the generation times are only a few months; and large clutches of big embryos are produced (100–1000 per mating). The embryos develop externally and are nearly transparent, facilitating microscopy, experimental manipulations, and screening for morphological mutants. High-density genetic linkage maps have been produced for visible and DNA markers, and the genome is being sequenced. Several useful genetic tools have been developed. Large-scale mutagenesis screens have detected genes involved in morphogenesis and other developmental processes ( 1 , 2 ). These screens involved a classical three-generation crossing strategy to detect recessive lethal mutations revealed in homozygous diploid mutants. Similar screens are done using insertional mutagenesis to facilitate cloning of the disrupted genes ( 3 ). Many useful molecular markers of differentiating cells have been characterized, and gene expression can be effectively manipulated by the use of morpholino antisense oligonucleotides or expression of dominant-negative mutant proteins. Much information concerning zebrafish mutants, strains, and methods can be found at http://www.zfin.org . These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".