MétaCan
Menu
Back to cohort
Record W1653313409 · doi:10.11425/sst.3.87

Developing a micro-bubble generator and practical system for purifying contaminated water

2014· article· ja· W1653313409 on OpenAlex

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

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typearticle
Languageja
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsFuture Earth
Fundersnot available
KeywordsBubbleContaminationEnvironmental scienceContaminated waterInflowClean waterEnvironmental engineeringPollutantGenerator (circuit theory)Waste managementEngineeringChemistryEnvironmental chemistryGeologyMechanicsOceanographyPhysics

Abstract

fetched live from OpenAlex

This paper is about the development of a system that purifies contaminated water with micro-bubbles for solutions of water pollutions such as industrial waste water, rivers, lakes, dams, ground water and ocean. The system is able to generate micro-bubbles from contaminated water by a micro-bubble generator. This micro-bubble generator injects micro-bubbles into contaminated water in a contaminated tank and the micro-bubbles separate the pollutants from clean water in a surface tank. For other systems, it is impossible to generate micro-bubbles into contaminated water directly, the inflow must be separate. However, the system introduced in this paper simplifies the process and makes direct injection possible.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
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 score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.300
GPT teacher head0.518
Teacher spread0.218 · 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