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Record W4281625660 · doi:10.18280/i2m.210202

Investigation of Using Physical Optical Reflectivity Probes in Evaluating and Monitoring Powder Mixtures of Sugar and Slag

2022· article· en· W4281625660 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

VenueInstrumentation Mesure Métrologie · 2022
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceSugarIntensity (physics)OpticsLight intensityReflectivitySlag (welding)Composite materialCalibrationMineralogyAnalytical Chemistry (journal)ChemistryChromatographyMathematics

Abstract

fetched live from OpenAlex

A preliminary investigation of some factors which can affect the reflected light intensity from granular and icing sugar has been carried out using an end viewing hemispherical tip probe. It is found that the reflectance is strongly dependent on the size range of the sugar particles, with the finer particles being more reflective. This property could be very useful in monitoring segregation in mixtures of mono-colored powders having different size distributions. Force applied to the probe will also affect the intensity readings. A layered mixture of sugar and slag powder was used to compare the sampling performance of the above probe with a side viewing wedge tip probe. Calibration curves for reflected light intensity versus percent slag concentration are obtained for two types of slag.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.328

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 head0.069
GPT teacher head0.341
Teacher spread0.272 · 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