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Record W6967384611 · doi:10.5281/zenodo.11142679

Data from: Fatty acid composition as a function of latitude in barnacle cyprid larvae

2024· dataset· en· W6967384611 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedataset
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsSt. Francis Xavier UniversityArcticNetUniversité du Québec à Rimouski
FundersEuropean Commission
KeywordsBarnacleFatty acidLarvaAcornPelagic zoneLatitude

Abstract

fetched live from OpenAlex

In this study, we investigated the fatty acid composition of the non-feeding stage of barnacle larvae (cyprids) using an integrative (larvae–environment) and comparative (latitudinal) approach. We measured fatty acids in the pelagic particulate matter and cyprids from Chthamalus bisinuatus, C. proteus, and Semibalanus balanoides from tropical to polar (Arctic) latitudes to identify potential food sources during the feeding larval stages (nauplius) that precede the cyprids and to ascertain larval capacity to integrate neutral (energetic) and polar (structural) fatty acids. Here we provide the complete dataset of all fatty acids detected both in i) the total particulate matter (TPM) present in the water column, and ii) the cyprid larvae of the different barnacle species. This could be useful in comparing data with future studies investigating fatty acid trophic markers in nearshore habitats. Raw data of biophysical paramateres includes cyprid i) size, ii) supply and (iii) settlement, as well as temperature collected using waterproof loggers (HOBO Pendant® Temperature/Light 64K). Image provided corresponds to the cyprid of the acorn barnacle Semibalanus balanoides, showcasing multiple lipid droplets, ie., the cyprid's main lipid storage organelles that store fat in the form of neutral lipids.

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)0.000
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: Dataset · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.079
GPT teacher head0.270
Teacher spread0.191 · 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
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
Published2024
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicHistory of Medicine StudiesFrench-language works237,207