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Record W2604522924

Spatial variability of Inherent Optical Properties in the perialpine lakes

2016· article· en· W2604522924 on OpenAlexaboutno aff
Nader Nakhaei, D. Boegman, Damien Bouffard

Bibliographic record

VenueInfoscience (Ecole Polytechnique Fédérale de Lausanne) · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsHypolimnionThermoclineOxygenFlux (metallurgy)BuoyancyStratification (seeds)Atmospheric sciencesEnvironmental scienceLimiting oxygen concentrationTurbulenceHydrology (agriculture)Materials scienceGeologyChemistryOceanographyMeteorologyThermodynamicsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Vertical flux of oxygen in lakes can play an important role in regulating the severity of hypoxia. Direct measurement of oxygen flux has remained hard due to lack of sufficient data. In this research, we focus on measuring vertical oxygen flux in a small hypoxic Canadian Shield lake using Fick’s Law = −K dDO⁄dz, where is the vertical turbulent diffusivity and () the vertical concentration of dissolved oxygen. To compute oxygen flux, a fast-response temperature and optical oxygen logger was attached to a temperature microstructure profiler and casts were obtained throughout the summer stratification period. The profiles were synchronized by aligning the temperature channels from the two instruments. To solve Fick’s Law, was obtained from the microstructure data using a buoyancy Reynolds number parameterization and ⁄ was obtained from the oxygen logger. The results show negligible oxygen flux through the thermocline (~ 3 × 10-4 gm-2d-1) during the summer stratification period, in comparison to the oxygen sinks in the hypolimnion (sediment oxygen demand and respiration).

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)0.002
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 score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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