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Record W2375733954

Research Progress of Amidoxime Chelating Resin

2014· article· en· W2375733954 on OpenAlexaff
Xue Le-l

Bibliographic record

VenueDevelopment and Application of Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsScience North
Fundersnot available
KeywordsChelationAdsorptionChelating resinMetal ions in aqueous solutionMaterials scienceWastewaterMetalSelectivityCharacterization (materials science)Heavy metalsNuclear chemistryChemistryWaste managementOrganic chemistryMetallurgyNanotechnologyEnvironmental chemistryCatalysis
DOInot available

Abstract

fetched live from OpenAlex

Amidoxime chelating resin,for its high selectivity and large adsorption capacity to heavy metal ions,can be used for wastewater treatment and recycling of heavy metal ions of waste ore,waste liquid. This article describes the amidoxime chelating resin synthesis method,physico-chemical properties and characterization tools. Present situation of study on adsorption and separation of materials,application prospect of amidoxime chelating resin are also covered.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.281
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2014
Admission routes1
Has abstractyes

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