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Modern Chironomid Assemblages and Their Relationship to Physical and Chemical Variables in Southwest Yukon and Northern British Columbia Lakes

2004· article· en· W2179710614 on OpenAlexafffundabout
S. Wilson, Konrad Gajewski

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChironomidaeLoss on ignitionEcologySedimentOrganic matterProductivityChironomusEnvironmental scienceOceanographyHydrology (agriculture)GeologyBiologyEnvironmental chemistryGeomorphologyChemistry

Abstract

fetched live from OpenAlex

Modern chironomid assemblages consisting of 68 taxa were extracted from the sediments of 39 lakes in southwest Yukon and northern British Columbia, Canada. Important factors accounting for the distribution of the chironomid taxa include sediment organic matter (LOI; weight-loss-on-ignition), total phosphorus, bottom water temperature, and lake alkalinity. The results show the importance of organic matter, which is associated with water depth and lake productivity, in affecting chironomid community composition. Tanytarsus sp. C, Tanytarsus pallidicornis type, Allo/Mesopsectrocladius, Polypedilum, and Procladius were associated with lakes having high LOI values and shallow lake depths, while Paratanytarsus, Sergentia, and Corynocera oliveri type were more prevalent in deeper lakes with more minerogenic sediments. Surprisingly, Chironomus was most abundant in deeper lakes with low LOI values, which might be partially explained by low oxygen levels. Contrary to some findings, Tanytarsus lugens group was common in shallow, productive lakes in this region.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.301
Threshold uncertainty score0.605

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.026
GPT teacher head0.265
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2004
Admission routes3
Has abstractyes

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