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Record W2066586787 · doi:10.1111/2041-210x.12020

Avoiding fishy growth curves

2013· article· en· W2066586787 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMethods in Ecology and Evolution · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIndeterminate growthStatisticsGrowth curve (statistics)Growth rateLogarithmBiologyMathematicsExtinction (optical mineralogy)Equivalence (formal languages)EconometricsEcology

Abstract

fetched live from OpenAlex

Summary Somatic growth is a fundamental property of living organisms, and is of particular importance for species with indeterminate growth that can change in size continuously throughout their life. For example, fishes can increase in size by 2–6 orders of magnitude during their lifetime, resulting in changes in production, consumption and function at the ecosystem scale. Within species, growth rates are traded off against other life‐history parameters, hence an accurate description of growth is essential to understand the comparative demography, productivity, fisheries yield and extinction risk of populations and species. The growth trajectory of indeterminate growing sharks and rays (elasmobranchs) and bony fishes (teleosts) is usually modelled using a three‐parameter logarithmic function, the von Bertalanffy growth function ( VBGF ), to describe the total length of the average individual at any given age. Recently, however, a two‐parameter form has gained popularity. Rather than being estimated in the model fitting process, the third y‐intercept parameter ( L 0 ) of the VBGF has been interpreted as being biologically equivalent to, and thus fixed as, the empirically estimated size at birth. We tested the equivalence assumption that L 0 is the same or similar to size at birth by comparing empirical estimates of size at birth available from the literature with estimates of L 0 from published data from elasmobranchs, and found that even though there is an overlap of values, there is a high degree of variability between them. We calculate the bias in the growth coefficient ( k ) of the VBGF by comparison between the two‐ and three‐parameter estimation methods. We show that slight deviations in fixed L 0 can cause considerable bias in growth estimates in the two‐parameter VBGF while providing no benefit even when L 0 matches the true value. We show that the effect of this biased growth estimate has profound consequences for fisheries stock status. We strongly recommend the use of the three‐parameter VBGF and discourage use of the two‐parameter VBGF because it results in substantially biased growth estimates even with slight variations in the value of fixed L 0 .

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.287
Teacher spread0.273 · 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