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Record W2121438871 · doi:10.14430/arctic4264

The Freshwater Copepod <i>Limnocalanus macrurus</i> in the Canadian Arctic Archipelago: Numbers, Weights, and Respiration Observed from September 1961 – July 1962

2013· article· en· W2121438871 on OpenAlexvenueaboutno aff
Spencer Apollonio, Jasmine E. Saros

Bibliographic record

VenueARCTIC · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsCopepodArcticArctic charArchipelagoOceanographyEnvironmental sciencePopulationEcologyPhysical geographyAnimal scienceGeographyBiologyAtmospheric sciencesFisherySalvelinusGeologyCrustaceanFish <Actinopterygii>Demography

Abstract

fetched live from OpenAlex

Numbers, weights, and oxygen consumption of the copepod Limnocalanus macrurus were measured through the winter 1961 – 62 under the ice of Immerk Lake on Devon Island, Arctic Canada. Maximum abundance was 2361 animals per m3 found under ice in mid June, average adult wet weight was 65 μg, and hourly oxygen consumption per adult ranged from 0.26 μg in late summer to 0.03 μg in early winter. The results are compared with results from Char Lake and Resolute Lake on Cornwallis Island, Arctic Canada. The Immerk population was more stable than those at the other lakes, and weights and oxygen consumption appear to be comparable. The seasonal breeding cycle at Immerk Lake was different from that at Char Lake and similar to that at Resolute Lake. A comparison of Immerk Lake data from 1961 – 62 and 1972 – 73 showed almost identical levels of total oxygen metabolism. Immerk Lake copepod oxygen consumption was 6.5% of the total lake metabolism, while that at Char Lake was 6%. These data may assist in future assessment of climate or anthropogenic changes.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.015
GPT teacher head0.185
Teacher spread0.170 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2013
Admission routes2
Has abstractyes

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Same venueARCTICSame topicMarine and coastal ecosystemsFrench-language works237,207