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Record W2612972216 · doi:10.1093/plankt/fbx022

Variability in Calanus finmarchicus egg production rate measurements: methodology versus reality

2017· article· en· W2612972216 on OpenAlexaffabout
Erica Head, Marc Ringuette

Bibliographic record

VenueJournal of Plankton Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsCalanus finmarchicusDiel vertical migrationCopepodIncubationPlanktonChlorophyll aCalanusBiologyPhytoplanktonOceanographyAnimal scienceEcologyEnvironmental scienceCrustaceanBotanyGeology

Abstract

fetched live from OpenAlex

Egg production rates (EPRs) for freshly caught female Calanus finmarchicus increase with increasing in situ chlorophyll concentration to upper limits, but with considerable scatter for individual points around fitted curves. Here, using time course experiments, we investigated whether females exhibit synchronous diel egg-laying behaviour, leading to variations in measured EPRs for different experimental start times. Also, we compared 24 h EPRs from these experiments with results obtained using two other standard 24 h incubation methods. We found (i) female C. finmarchicus from the Labrador Sea did not exhibit diel egg-laying behaviour in spring, (ii) egg-laying was sometimes more frequent during the first 6 h of incubation than thereafter and (iii) standard 24 h incubations underestimated EPRs in 20–36% of experiments due to egg loss. Using results from this and a previous study Head et al. [(2013a) Characteristics of egg production of the planktonic copepod, Calanus finmarchicus, in the Labrador Sea: 1997–2010. J. Plankton Res. 35, 281–298] we developed a new expression relating in situ EPRs to chlorophyll concentration, temperature, female size and season. Season is represented by empirically derived coefficients, which vary regionally reflecting differences in spring bloom dynamics. For 100 experimental stations predicted and measured EPRs were highly correlated (r2 = 0.56, P < 0.001). Additional sources of variability are discussed and recommendations are made regarding EPR measurement methods.

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)0.034
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.441
GPT teacher head0.476
Teacher spread0.036 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2017
Admission routes2
Has abstractyes

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