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Record W2045997220 · doi:10.1007/s00267-010-9484-4

Defining Chlorophyll-a Reference Conditions in European Lakes

2010· article· en· W2045997220 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Management · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsMinistry of Environment
FundersJoint Research CentreEuropean Commission
KeywordsNature ConservationEnvironmental scienceChlorophyllForest managementForestryGeographyEcologyAgroforestryBotanyBiology

Abstract

fetched live from OpenAlex

The concept of "reference conditions" describes the benchmark against which current conditions are compared when assessing the status of water bodies. In this paper we focus on the establishment of reference conditions for European lakes according to a phytoplankton biomass indicator--the concentration of chlorophyll-a. A mostly spatial approach (selection of existing lakes with no or minor human impact) was used to set the reference conditions for chlorophyll-a values, supplemented by historical data, paleolimnological investigations and modelling. The work resulted in definition of reference conditions and the boundary between "high" and "good" status for 15 main lake types and five ecoregions of Europe: Alpine, Atlantic, Central/Baltic, Mediterranean, and Northern. Additionally, empirical models were developed for estimating site-specific reference chlorophyll-a concentrations from a set of potential predictor variables. The results were recently formulated into the EU legislation, marking the first attempt in international water policy to move from chemical quality standards to ecological quality targets.

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.

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 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 score0.296
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.007

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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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