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Record W7024541710

To stay or not to stay? A model to test decision making of Mysis diluviana to vertically migrate

2020· article· en· W7024541710 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks -A service of University of Vermont Libraries (University of Vermont) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPelagic zoneDiel vertical migrationBenthic zonePredationPopulationMysidacea
DOInot available

Abstract

fetched live from OpenAlex

Freshwater mysids play vital roles in lake food webs because their extensive diel vertical migration (DVM) couples pelagic and deep-water benthic habitats. Mysids are omnivorous and thus have the potential to transport nutrients in both vertical directions, and also, serve as a vital food source for many pelagic and benthic fishes. Recent observations indicate that Mysis spp exhibit partial DVM (pDVM) where a percentage of the population remains benthic at night. The drivers that determine if mysids migrate at night remain unknown. A model was developed to evaluate how decisions to migrate or remain on the bottom at night, and the potential drivers that could influence those decisions, can lead to population-level pDVM behavior. The model runs on hourly time step and includes seasonal changes in light, temperature, food availability, and habitat-dependent mortality. We used the model to test several hypotheses about Mysis decision making including: (1) pelagic food availability; (2) size-based predation risk; and (3) body condition (reproductive state). The model will be compared with empirical observations on pDVM in Lakes Champlain and Ontario. Results from the model will be used to guide hypothesis development and quantify effects of alternative migration strategies on Mysis survival and growth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.004
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 head0.019
GPT teacher head0.204
Teacher spread0.185 · 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 teacher head, not a consensus.

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueScholarWorks -A service of University of Vermont Libraries (University of Vermont)Same topicFish Ecology and Management StudiesFrench-language works237,207