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Rock Alteration and its Relation to Surface Finishing

2013· article· en· W2038254818 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

VenueKey engineering materials · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsnot available
Fundersnot available
KeywordsPetrographyGeologySilicateGeochemistryTexture (cosmology)MineralMineralogyFeature (linguistics)MetallurgyMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Rock finishing is a valuable tool used by architects to improve contrasts in decoration pattern in walls or building façades as they exhibit textures and color differences on their surfaces according to the type of finishing. When exposed to aggressive environment, these finishing impose different rate of alteration in the rocks as their ability to absorb humidity is also different for each type of finishing. Special types of silicate rocks underwent experiments in order to test their response to salt fog atmosphere. The study was centered on surface aspects of polished and honed finishing and their mass loss during seven salt fog cycles. All rocks studied are identified in the rock industry as granites although some are differently classified according to their petrography. They are: Blue Bahia, Belfast, Amazonite, Baltic Brown, Imperial Brown and Blue Labrador “Granites”. Each one has a particular feature to justify its inclusion in the study, as texture, mineral composition or specific occurrence and mineral association.

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 categoriesInsufficient payload (model declined to judge)
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 score0.733
Threshold uncertainty score1.000

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)0.0010.000

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 head0.010
GPT teacher head0.174
Teacher spread0.163 · 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