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Studies Regarding Primary Succession in a Mine Tailing Pond from Bozanta, Maramureș County

2020· article· en· W3035694018 on OpenAlexaff
Aurel MAXIM, Tania Mihăiescu, Teodor Rusu, V. Roman, Andrei Stoie, Mignon Şandor, Larisa BÎLC, Lucia Mihălescu, Razvan BENDRE

Bibliographic record

VenueBulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Agriculture · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil and Environmental Studies
Canadian institutionsScience North
Fundersnot available
KeywordsPhragmitesDominance (genetics)Herbaceous plantTailingsHumusEcological successionPopulationEnvironmental scienceVegetation (pathology)Abundance (ecology)EcologyBotanySoil waterChemistryBiologyWetland

Abstract

fetched live from OpenAlex

The objective of this study is to carry out a vegetation study at the Bozanta’s tailing pond, located 5 km away from Baia-Mare.Between 2016 and 2017, using the metric frame, the existing species were identified and the following phytocenothic and population indices were determined: presence, frequency, presence classes, and the average abundance-dominance. Soil samples were taken to perform the following physico-chemical analyses: pH, P, K, N, humus and heavy metals.The floral inventory shows the presence of six tree species, four species of and 30 herbaceous species. Eleven years after the pond closure, the surface is covered with: 30% vegetation coverage, 35% water gloss and the 35% difference is occupied by arid. The average abundance-dominant synthetic indicator showed that the highest coverage is found in Betula pendula, Salix caprea, and in the grass species, Phragmites australis.The results of physicochemical analyses of the substrate showed very wide ranges of pH and different amounts of phosphorus, potassium and humus, and low amounts of nitrogen. The presence and concentration of the following heavy metals were determined from three samples: Cd, Pb, Ni, Cr. In regards to lead and chromium level, the alert threshold has not been reached.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.041
GPT teacher head0.218
Teacher spread0.177 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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