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Record W836129536 · doi:10.1163/1937240x-00002365

Variation in the size and composition of ejaculates produced by male American lobsters, Homarus americanusH. Milne Edwards, 1837 (Decapoda: Nephropidae)

2015· article· en· W836129536 on OpenAlexaff
Tracy L. Pugh, Michel Comeau, Winsor H. Watson, Kadra Benhalima

Bibliographic record

VenueJournal of Crustacean Biology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsFisheries and Oceans Canada
FundersCisco Systems
KeywordsBiologyCarapaceDecapodaSpermHomarusAnimal scienceSpermatogenesisReproductionAnomuraAnatomyCrustaceanAmerican lobsterSpermatophoreSpermatozoonZoologyEcologyEndocrinologyBotany

Abstract

fetched live from OpenAlex

Variation in the quality of ejaculate produced by male American lobsters, Homarus americanusMilne Edwards, 1837, has been previously described, but never quantified. This study examined the size and composition of ejaculates produced by 111 males ranging from 60 to |$108\,{\rm{mm}}$| in carapace length (CL). Ejaculates were obtained via electrical stimulation, photographed and then processed for histology. Half of the males produced an ejaculate from each gonopore, 29% produced only one ejaculate, and the remainder (21%) produced none. Males as small as |$64\,{\rm{mm\, CL}}$| produced an ejaculate containing sperm. Ejaculate weight increased with male size, but there was a negative relationship between ejaculate weight and the percent of the ejaculate that was composed of sperm mass. Variation observed in the size and composition of ejaculates produced by similarly-sized males indicates that not all males invest equally in reproduction. Additionally, larger males may invest disproportionately more in the sperm plug (acellular component), possibly as paternal assurance.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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

Citations18
Published2015
Admission routes1
Has abstractyes

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