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Record W15931961 · doi:10.1007/s10646-004-6262-1

VARIJABILNOST POPULACIJA BIJELE ( Alnus incana /L./ Moench) I CRNE JOHE ( A . glutinosa /L./ Gaertn.) NA PODRUČJU MURE I DRAVE PREMA MORFOLOŠKIM OBILJEŽJIMA LISTOVA

2014· article· en· W15931961 on OpenAlexaboutno aff
Igor Poljak, Marilena Idžojtić, Irena Šapić, Joso Vukelić, Marko Zebec

Bibliographic record

VenueŠumarski list · 2014
Typearticle
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsAlnus glutinosaHorticultureBiologyBotanyPhysicsAlder

Abstract

fetched live from OpenAlex

We report on an inventory and analysis of sediment mercury (Hg) concentrations from 579 sites across northeastern North America. Sediment Hg concentrations ranged from the limit of detection ca. 0.01-3.7 microg g(-1) (dry weight, d.w.), and the average concentration was 0.19 microg g(-1) (d.w.) Sediment methylmercury concentrations ranged from 0.15 to 21 ng g(-1) (d.w.) and the mean concentration was 3.83 ng g(-1) (d.w.). Total Hg concentrations (HgT) were greatest in lakes > reservoirs > rivers, although the proportion of Hg as methylmercury showed an inverse pattern. Total Hg was weakly and positively correlated with the sediment organic matter and percent of watershed as forested land, and weakly and negatively correlated with sediment solids content, drainage area, and agricultural land. Sediment methylmercury concentrations were weakly and positively correlated to wetland area, and weakly and negatively correlated to drainage area. Methylmercury, expressed as a percentage of HgT was positively correlated to agricultural land area. For sites with co-located sediment and fish-tissue sampling results, there was no relationship between sediment Hg and fish-tissue Hg. Finally, our data indicate that at least 44% of waters across the region have sediment HgT concentrations in excess of Canadian and United States minimum sediment contaminant guidelines for the protection of aquatic biota.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.214
Teacher spread0.205 · 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 designBench or experimental
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

Citations5
Published2014
Admission routes1
Has abstractyes

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