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The New Zealand common smelt: biology and ecology

2005· article· en· W2067733764 on OpenAlexaff
F. J. Ward, T. G. Northcote, J Boubee

Bibliographic record

VenueJournal of Fish Biology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
Fundersnot available
KeywordsSmeltSpawn (biology)Fish migrationBiologyFisheryPredationEcologyForage fishFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The common smelt is one of the most widespread indigenous freshwater fishes in New Zealand. One other member of the family Retropinnidae, Stokellia anisodon (Stokell), is present but is confined to a small region of the South Island. There are many diadromous as well as river and lake resident populations, the latter, sometimes a result of introductions to serve as forage fish for trout. Diadromous smelt spawn during austral autumn–winter on sand bars of lower riverine reaches. Larval stages inhabit coastal marine waters, and the postlarvae to immature stages re‐enter rivers and some lowland lakes. Diadromous smelt are distinguished from lowland lake resident forms by high vertebral but low gill raker numbers and larger size and from those present in some isolated waters, by high vertebral numbers alone. Lake or reservoir resident smelt usually spawn in austral spring–summer on sandy shallows at stream mouths or along shorelines. Verified smelt ages (otolith analyses) indicate that in some populations most smelt mature and spawn after c. 1 year. Adult smelt feed on a spectrum of primarily invertebrate animals ranging from small zooplankters to insects and occasionally small fishes. Smelt are a major prey for both brown trout and rainbow trout. Adult smelt are a minor food for the Maori people. As postlarvae they are a component of a few ‘whitebait’ fisheries. Most smelt populations are increasingly affected by environmental changes induced by human activities. Although many studies have examined problems affecting smelt, further effort is required, along with more basic research.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.441

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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

Citations87
Published2005
Admission routes1
Has abstractyes

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