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Record W2800577744 · doi:10.1071/mf17198

Habitat use and movements of Australian grayling (Prototroctes maraena) in a Victorian coastal stream

2018· article· en· W2800577744 on OpenAlexaff
David Dawson, Wayne M. Koster

Bibliographic record

VenueMarine and Freshwater Research · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsDawson College
FundersMelbourne Water
KeywordsGraylingFish migrationThreatened speciesHabitatFisheryEcologyGeographyFaunaRange (aeronautics)BiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Riverine fishes are among the most imperilled fauna in the world; however, for many species, there is little or no understanding of their ecological requirements. The Australian grayling (Prototroctes maraena) is a small diadromous fish endemic to rivers in south-eastern Australia that has declined considerably in range and abundance and is listed as threatened nationally. To improve understanding of the species’ movement ecology and to inform the development of conservation management actions, we examined the day-to-day movements and habitat use of Australian grayling (n = 7) over 8 weeks by using radio-telemetry. Tagged individuals of Australian grayling typically occupied restricted (i.e. tens to hundreds of metres) reaches of stream, and were mostly located in moderate- to fast-flowing habitats (i.e. glide or run), although, at night, use of slower-flowing habitats (i.e. pools) increased. They also undertook longer-distance downstream movements during a period of increased streamflow. Incorporation of such information into management strategies has the potential to improve our capacity to maintain or re-instate the conditions required to conserve and restore Australian grayling populations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.044
GPT teacher head0.300
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2018
Admission routes1
Has abstractyes

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