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Record W2784263650 · doi:10.1139/cjce-2017-0183

Investigation of alternative ways for recycling waste foundry sand: an extensive review to present benefits

2018· article· en· W2784263650 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicMaterials Engineering and Processing
Canadian institutionsnot available
Fundersnot available
KeywordsFoundrySand castingWaste managementCastingEngineeringEnvironmental scienceMunicipal solid wasteMoldMetallurgyMaterials science

Abstract

fetched live from OpenAlex

Foundry sand, an indispensable component of the metal casting process, is discarded after a number of metal casting operations. Virgin sand is then required for any new casting processes, and the spent foundry sand is treated as waste, resulting in huge amounts of discarded sand being either stockpiled or dumped into landfills. This results in a wide scale consumption of natural resources despite the fact that this “waste” can be recycled as a viable resource in various engineering processes. To this end, this study represents a detailed investigation into the possible uses for waste foundry sand. Obtained results concluded that this material can best be utilized in highway and hydraulic barrier construction, as well as low strength concrete production. Thus, the recycling of waste foundry sand results in the conservation and saving of natural and financial resources.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.530
Threshold uncertainty score0.788

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 head0.036
GPT teacher head0.236
Teacher spread0.200 · 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