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Record W4312961107 · doi:10.56588/iabcd.v1i1.12

PHYTOEXTRACTION OF ARSENIC AND BORON AND ITS EFFECT ON GROWTH PARAMETERS OF TAGETES ERECTA L.

2022· article· en· W4312961107 on OpenAlex
Kirti Pandya, Sanjukta Rajhans, Himanshu Pandya, Archana Mankad

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

VenueInternational Association of Biologicals and Computational Digest · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFlowering Plant Growth and Cultivation
Canadian institutionsImpact
Fundersnot available
KeywordsHyperaccumulatorPhytoremediationHydroponicsTagetesArsenicHorticultureBoronHeavy metalsBotanyChemistryEnvironmental scienceEnvironmental chemistryBiology

Abstract

fetched live from OpenAlex

Tagetes erecta L. was used to explore the use of hydroponics technique for phytoremediation. The treatment of heavy metals such as Arsenic and Boron was provided to the plants of marigold. Various experiments conducted have shown the use of marigold as a plant species with hyperaccumulator capacity. In the present study the plants were given treatments of heavy metals for a period of 20 days. Growth analysis was carried out at the interval of 5 days and the data was recorded. This paper has focused on changes in the growth parameters in proportion to the heavy metal treatment provided. Here, hydroponics technique was used as an alternative to the soil media.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.152

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)0.0000.000

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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