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Record W7042063908

A palaeolimnological study of Tugulnuit Lake, British Columbia, Canada, with special emphasis on river influence as recorded by chironomids in the lake's sediment

2018· other· en· W7042063908 on OpenAlexaboutno aff

Bibliographic record

VenuereroDoc Digital Library · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersUniversité de FribourgAlbert-Ludwigs-Universität Freiburg
KeywordsNucleofectionFusible alloyHyporeflexiaGestational periodTSG101Subpoena
DOInot available

Abstract

fetched live from OpenAlex

Sediments from Tugulnuit Lake in the Okanagan Valley of British Columbia, Canada, were examined for chironomid assemblages. The chironomid stratigraphy obtained encompasses the last 4000 to 5000 years and suggests a warm and fairly stable climate typical for a temperate lake at low- to mid-elevation. This is indicated by the even distribution of warm-water taxa, such as Cladopelma, Dicrotendipes, Polypedilum, Pentaneurini, Stempellina, Stempellinella/Zavrelia and Pseudochironomus throughout the core. Very few cold-water taxa occurred in the sediments. However, stream inputs have had a major impact on Tugulnuit Lake. Sandy sediments and the appearance of Simuliidae and stream-inhabiting chironomid taxa (e.g., Brillia/Euryhapsis, Eukiefferiella/Tvetenia, Rheocricotopus) indicate that a stream intruded into the current lake's basin ca. 3800 yr Before Present (BP). Sediments deposited prior to, and after, the stream's intrusion show a distinctly different chironomid assemblage exhibiting chironomid taxa more typical for lentic habitats. This result indicates that chironomids can serve to detect past stream influences on lake environments. Thus, rheophilic chironomids preserved in lake cores provide a new alternative for reconstructing stream palaeoenvironmental records

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 score0.014
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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