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Record W6948637615 · doi:10.5061/dryad.ngf1vhhx8

Data from: Paternal hatching care regulates the timing, synchrony, and success of hatching in a coral reef fish

2022· dataset· en· W6948637615 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2022
Typedataset
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsGestational periodTSG101NucleofectionParaphernaliaPopulationProteogenomics

Abstract

fetched live from OpenAlex

In oviparous species, the timing of hatching is a crucial decision, but for developing embryos, assessing cues that indicate the optimal time to hatch is challenging. In species with parental care, parents can assess environmental conditions and induce their offspring to hatch. We provide the first documentation of parental hatching regulation in a coral reef fish, demonstrating that male neon gobies (Elacatinus colini) directly regulate hatching by removing embryos from the clutch and spitting hatchlings into the water column. All male gobies synchronized hatching within 2h of sunrise, regardless of when eggs were laid. Paternally-incubated embryos hatched later in development, more synchronously, and had higher hatching success than artificially-incubated embryos that were shaken to simulate paternal hatching cues or not stimulated. Artificially-incubated embryos displayed substantial plasticity in hatching times (range: 88 – 244 hours post-fertilization), suggesting that males could respond to environmental heterogeneity by modifying the hatching time of their offspring. Finally, paternally-incubated embryos hatched with smaller yolk sacs and larger propulsive areas than artificially-incubated embryos, suggesting that paternal effects on hatchling phenotypes may influence larval dispersal and fitness. These findings highlight the complexity of fish parental care and may have important, and currently unstudied, consequences for fish population dynamics.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0070.006
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.000

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 head0.222
GPT teacher head0.402
Teacher spread0.180 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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