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Record W3005923445 · doi:10.1002/lol2.10135

Paired O<sub>2</sub>–CO<sub>2</sub> measurements provide emergent insights into aquatic ecosystem function

2020· article· en· W3005923445 on OpenAlexafffund
Dominic Vachon, Steven Sadro, Matthew J. Bogard, Jean‐François Lapierre, Helen M. Baulch, James A. Rusak, Blaize A. Denfeld, Alo Laas, Marcus Klaus, Jan Karlsson, Gesa A. Weyhenmeyer, Paul A. del Giorgio

Bibliographic record

VenueLimnology and Oceanography Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité du Québec à MontréalQueen's UniversityMinistry of the Environment, Conservation and ParksUniversity of SaskatchewanUniversité de MontréalUniversity of Lethbridge
FundersMinistère de l’Environnement, de la Protection de la nature et des ParcsKempestiftelsernaGlobal Lake Ecological Observatory NetworkKnut och Alice Wallenbergs StiftelseVetenskapsrådetNational Science FoundationEesti TeadusagentuurSvenska Forskningsrådet Formas
KeywordsAquatic ecosystemEcosystemEnvironmental scienceWetlandEcologyComputer scienceBiology

Abstract

fetched live from OpenAlex

Scientific Significance Statement Metabolic stoichiometry predicts that dissolved oxygen (O 2 ) and carbon dioxide (CO 2 ) in aquatic ecosystems should covary inversely; however, field observations often diverge from theoretical expectations. Here, we propose a suite of metrics describing this O 2 and CO 2 decoupling and introduce a conceptual framework for interpreting these metrics within aquatic ecosystems. Within this framework, we interpret cross‐system patterns of high‐frequency O 2 and CO 2 measurements in 11 northern lakes and extract emergent insights into the metabolic behavior and the simultaneous roles of chemical and physical forcing in shaping ecosystem processes. This approach leverages the power of high‐frequency paired O 2 –CO 2 measurements, and yields a novel, integrative aquatic system typology which can also be applicable more broadly to streams and rivers, wetlands and marine systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.179
Teacher spread0.162 · 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

Citations100
Published2020
Admission routes2
Has abstractyes

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