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Record W2096271410 · doi:10.1657/1938-4246-46.2.293

Temporal and Spatial Dynamics of Ice-Covered Upper Dumbell Lake (Ellesmere Island, Arctic Canada) during the Summer of 1959

2014· article· en· W2096271410 on OpenAlexaboutno aff
Spencer Apollonio, Jasmine E. Saros

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsZooplanktonOceanographyChlorophyll aEnvironmental scienceArcticAlkalinityBiomass (ecology)NitratePrimary productionNutrientEcologyEcosystemChemistryBiologyGeologyBotany

Abstract

fetched live from OpenAlex

Abstract We report on a limnological study of ice-covered Upper Dumbell Lake (Ellesmere Island, Canada) conducted during the summer of 1959. The lake was vertically profiled for physical (temperature, light), chemical (alkalinity, pH, oxygen, nutrients), and biological (chlorophyll a, gross and net primary productivity) variables on 21 dates spanning from early July to early September. Zooplankton density and age structure were also determined on four dates. Factors such as temperature, alkalinity, pH, and oxygen varied little with depth or over time, whereas nutrients (nitrate, dissolved silica, soluble reactive phosphorus), light, chlorophyll a, and gross and net photosynthesis varied substantially. Comparing July to August, nitrate and light intensity decreased while dissolved silica, chlorophyll a, and gross and net primary production increased, with two distinct peaks in algal biomass occurring over the month of August. Chlorophyll a in this lake was negatively correlated with nitrate concentrations, suggesting uptake of nitrogen as algal biomass increased. The copepod Limnocalanus macrurus was the dominant zooplankton taxon present; the age structure of the population advanced over the summer. This study reveals the dynamic nature of vertical habitat gradients even under the ice of Arctic lakes and provides important baseline data for conditions in an Arctic lake during the mid-20th century.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.226
Teacher spread0.214 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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