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Record W2291280216 · doi:10.1021/acs.jchemed.5b00514

Flotation of Mineral and Dyes: A Laboratory Experiment for Separation Method Molecular Hitchhikers

2016· article· en· W2291280216 on OpenAlexaff
Tim Rappon, Jarrett A. Sylvestre, Manit Rappon

Bibliographic record

VenueJournal of Chemical Education · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsLakehead University
Fundersnot available
KeywordsExtraction (chemistry)WastewaterMineralMineral processingChemistryProcess engineeringBiochemical engineeringEnvironmental chemistryEnvironmental scienceChromatographyWaste managementEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Flotation as a method of separation is widely researched and is applied in many industries. It has been used to address a wide range of environmental issues including treatment of wastewater, recovery of heavy metals for recycling, extraction of minerals in mining, and so forth. This laboratory attempts to show how such a simple method can be used to separate chemicals and minerals. With flotation, particles (mineral or dye molecules) hitch a ride with air bubbles to the surface of the liquid. Students learn how the basic principles that they learn from theory can be applied to a significant method of separation that they can connect with their daily lives. This laboratory is easy to set up and requires only simple pieces of apparatus that can be purchased from household stores. Therefore, it can be prepared for teaching in virtually any chemistry laboratory in the world.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.008
GPT teacher head0.344
Teacher spread0.336 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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