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Record W4410814177 · doi:10.5751/ace-02853-200122

Survival of captive-raised light-footed Ridgway’s rails is influenced by release date and time in wild

2025· article· en· W4410814177 on OpenAlexvenueno aff
K. Sawyer, Courtney J. Conway

Bibliographic record

VenueAvian Conservation and Ecology · 2025
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceUniversity of Idaho
KeywordsEcologyCaptivityBiologyZoologyGeography

Abstract

fetched live from OpenAlex

Captive breeding and translocation programs are an increasingly common conservation tool and management strategy used for some of the rarest and most endangered species in the world. These programs come at a high cost, and many translocation programs fail to monitor animals after release. Light-footed Ridgway’s rails (<em>Rallus obsoletus levipes</em>) are federally endangered marsh birds endemic to coastal wetlands of southern California and northern Mexico. Juvenile captive-raised light-footed Ridgway’s rails have been released into marshes within their U.S. range for >20 yr, but little effort has been devoted to post-release tracking of their movement and survival. We used satellite GPS transmitters to track survival of 46 juvenile captive-released and 42 juvenile wild-caught light-footed Ridgway’s rails from 2020–2022. Our results suggest that juvenile captive-released rails had lower initial daily survival probability (0.979) compared with that of juvenile wild-caught rails (0.994). Survival probability of captive-released rails increased with time in the wild, matching that of wild birds at about 100 d post-release. Survival of captive-released birds was most influenced by the date birds were released (releases in early summer had the highest survival). Our study emphasizes the importance of post-release monitoring as part of any captive breeding and translocation program and provides important insight into management strategies that may improve captive-released rail survival in the wild.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.477

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)0.0000.000

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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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