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Record W2144894957 · doi:10.1080/03632415.2013.803472

Measurement Error in Fish Lengths: Evaluation and Management Implications

2013· article· en· W2144894957 on OpenAlex
Aaron J. Bunch, Carl J. Walters, Lewis G. Coggins

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.

Bibliographic record

VenueFisheries · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFish <Actinopterygii>FisheryStatisticsMathematicsBiology

Abstract

fetched live from OpenAlex

ABSTRACT A fundamental aspect of fisheries science is measuring body length. Humans are inherently prone to error despite systems and provisions made to reduce it. We evaluated length measurement error (herein, referred to as “error”) and digit preference from fish studies conducted on the Colorado River and Little Colorado River in Arizona. Empirical error estimates varied among fish species and generally increased with fish size. We identified a digit preference for numbers ending in zero and five, which was exacerbated with larger sizes. Error effects on growth estimates were largest for fish recaptured after a short time, and we suggest guarding against the error phenomenon by removing data from fish captured and recaptured within a minimum of 30 days. Human, situation, and specimen induced error factors are described. Fisheries professionals should be cognizant of error factors, especially in situations when high precision and accuracy are required and results have important management implications. RESUMEN un aspecto fundamental en las ciencias pesqueras es la medición de la talla corporal. Los humanos somos inherentemente propensos a cometer errores pese a los sistemas y medidas preventivas que se utilizan para reducirlos. En este trabajo se evalúa el error asociado a la medición de la talla (en lo sucesivo se le llamará “error”) y la preferencia en el número de dígitos en los estudios ícticos llevados a cabo en el Río Colorado y el Río Coloradito, Arizona. Los estimados empíricos del error variaron entre especies de peces y en general se incrementaron conforme la aumenta la talla de los peces. Se identificaron preferencias en cuanto al número de dígitos para los números con terminación cero y cinco, lo cual se amplificó en los peces más grandes. Los efectos del error en las estimaciones de crecimiento fueron más grandes en el caso de los peces recién recapturados. Se sugiere tratar el fenómeno del error mediante la remoción de los datos provenientes de peces recapturados en los primeros 30 días después de su liberación. Se describen los factores de error humano, de medición y asociado al espécimen. Los profesionales de las pesquerías deben ser conscientes de los factores de error, especialmente en situaciones en las que se requieren precisión y exactitud y cuando hay implicaciones importantes para el manejo.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.647
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0140.000

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 head0.058
GPT teacher head0.281
Teacher spread0.223 · 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