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Record W2039602811 · doi:10.1038/srep07484

Coral spawning in the Gulf of Oman and relationship to latitudinal variation in spawning season in the northwest Indian Ocean

2014· article· en· W2039602811 on OpenAlexfundno aff
Emily J. Howells, David Abrego, Grace O. Vaughan, John A. Burt

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
FundersMohammed bin Zayed Species Conservation FundZayed UniversityYork UniversityFord Motor Company
KeywordsCoralAcroporaReefOceanographyBiologyLatitudeCoral reefFull moonFisheryGeographyEcologyGeology

Abstract

fetched live from OpenAlex

Despite a wealth of information on sexual reproduction in scleractinian corals, there are regional gaps in reproductive records. In the Gulf of the Oman in the Arabian Sea, reproductive timing was assessed in four common species of broadcast spawning corals using field surveys of gamete maturity and aquarium observations of spawning activity. The appearance of mature gametes within the same month for Acropora downingi, A. hemprichii, Cyphastrea microphthalma and Platygyra daedalea (≥ 75% of colonies, n = 848) indicated a synchronous and multi-specific spawning season. Based on gamete disappearance and direct observations, spawning predominantly occurred during April in 2013 (75-100% of colonies) and May in 2014 (77-94% of colonies). The difference in spawning months between survey years was most likely explained by sea temperature and the timing of lunar cycles during late-stage gametogenesis. These reproductive records are consistent with a latitudinal gradient in peak broadcast spawning activity at reefs in the northwestern Indian Ocean which occurs early in the year at low latitudes (January to March) and progressively later in the year at mid (March to May) and high (June to September) latitudes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations53
Published2014
Admission routes1
Has abstractyes

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