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Record W2135700894 · doi:10.1086/317748

Experimental (Tamoxifen‐Induced) Manipulation of Female Reproduction in Zebra Finches (<i>Taeniopygia guttata</i>)

2000· article· en· W2135700894 on OpenAlexaff
Tony D. Williams

Bibliographic record

VenuePhysiological and Biochemical Zoology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTaeniopygiaYolkBiologyTamoxifenVitellogeninEndocrinologyOviductInternal medicineZebra finchEstrogenReproductionAntiestrogenEcologyGeneGeneticsMedicine

Abstract

fetched live from OpenAlex

Experimental manipulation of reproductive phenotype is a potentially powerful approach for understanding the fitness relationships of traits such as egg size, egg composition, and egg number. In this study, I investigated the effect of the antiestrogen tamoxifen on multiple, estrogen-dependent reproductive traits in female zebra finches (Taeniopygia guttata). Short-term tamoxifen treatment of egg-laying females (two daily injections before laying) had no effect on the timing or the pattern of egg laying compared to sham controls. However, tamoxifen treatment caused (1) a marked, but transient, decrease in egg size; (2) increased within-clutch egg-size variation; (3) a reduction in plasma vitellogenin (VTG) levels; and (4) lower dry yolk and yolk protein content of tamoxifen-treated females. Plasma levels of the second yolk precursor, very low density lipoprotein (VLDL), were not affected by tamoxifen, and tamoxifen appeared to have no effect on oviduct function in egg-laying females. These results are consistent with tamoxifen blocking estrogen receptors in the liver, suppressing VTG production, and decreasing the plasma pool of yolk precursors below a level required to maintain yolk formation at the normal rate. Tamoxifen treatment can therefore be used successfully to manipulate several components of the female reproductive phenotype (egg composition, intraclutch egg-size variation) to further explore the fitness consequences of these traits.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.253
Teacher spread0.214 · 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.

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

Citations30
Published2000
Admission routes1
Has abstractyes

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