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Record W2040324547 · doi:10.1002/col.20579

Measuring the color of granite rocks: A proposed procedure

2010· article· en· W2040324547 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueColor Research & Application · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsColorimeterColor differenceMeasure (data warehouse)MineralogyMathematicsStatisticsOpticsGeologyArtificial intelligenceComputer sciencePhysicsData mining

Abstract

fetched live from OpenAlex

Abstract In spite of color being one of the physicochemical parameters most commonly used to characterize ornamental stone, there is yet no standardized protocol for measuring this parameter. Such a protocol is of particular importance for characterizing the color of heterogeneous surfaces, as in the case of granite. The aim of the present study was to determine the minimum area and the number of measurements required to characterize the color of granite rocks. A spectrophotometer and a tristimulus colorimeter, were used to measure the color of granite samples, and the measurements were expressed in CIE L*a*b* color system units. Three parameters were considered as variable factors: the type of rock (Labrador Claro, Grissal, Rosa Porriño, and Blanco Cristal), surface finish (polished, honed, sawn, and flamed), and target area (circular apertures of diameter 5, 8, 10, and 50 mm). The results of the application of multivariate analysis of variance and of the classical CIELAB formula and CIE L*a*b*‐based color‐difference formulae (i.e., CIE94 and CIEDE2000) to the data revealed that, although all considered factors affected the minimal area and the number of measurements required, the different circular apertures of both the instruments can be disregarded if the number of measurements and area recommended in this study are used. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010

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)0.001
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 score0.739
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.100
GPT teacher head0.319
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