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Record W2334903907 · doi:10.5741/gems.43.2.120

Durability Testing of Filled Emeralds

2007· article· en· W2334903907 on OpenAlexaboutno aff
Mary L. Johnson

Bibliographic record

VenueGems & Gemology · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMineralogy and Gemology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDurabilityGeologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Researchers treated 128 emeralds with nine emerald fillers-Araldite 6010, cedarwood oil, paraffin oil, unhardened and surface-hardened Opticon, a mixture of cedarwood oil and Canada balsam, surface-hardened Norland Optical Adhesive 65, and the solid fillers Gematrat and Permasafeand then exposed them (along with 14 unfilled emeralds) to common conditions of wear and cleaning.All emeralds were held for about six years, and most were then subjected to one of the following durability tests: exposure to long-wave UV radiation (a component of sunlight), to mild heat and incandescent light in a display case, to five chill-thaw cycles, and to a desiccation environment; ultrasonic cleaning with either warm water or BCR; and cleaning with steam or mild chemical solvents.Changes were evident in about 35% of the filled emeralds after the mild exposure tests (i.e., time, UV radiation, display case); those with liquid fillers were especially susceptible.The desiccation environment made fissures visible in a majority of emeralds.Hard fillers damaged their host emeralds by expanding cracks during durability testing, while chill-thaw cycling extended cracks in both filled and unfilled emeralds.Emeralds with liquid fillers were most susceptible to appearance changes due to ultrasonic cleaning and exposure to ethanol or acetone.Some observations on the effectiveness of different fillers on emerald appearance are also provided.Colombia, paraffin oil (mineral oil) in Zimbabwe and Zambia, and Opticon in Brazil (see, e.g., Ringsrud, 1983;Kammerling et al., 1991;Koivula et al., 1993 Koivula et al., , 1994a;;Kennedy, 1998; for more on the history of emerald filling, see the G&G Data Depository at www.gia.edu/gemsandgemology).Although these practices require disclosure, for many years fillers were used to enhance the appearance of emeralds without much public comment.In the 1990s, however, controversies erupted over the use of epoxies and similar substances to fill emeralds, as little was known about their durability and they were considered synthetic or "unnatural" by some in the trade.When these controversies were brought to the attention of consumers (see, e.g., Costanza, 1998; "Jewelry scene…," 1998), most of whom did not know that emeralds are customarily filled, the emerald market plummeted (see, e.g., Drucker, 1999).

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.028
GPT teacher head0.243
Teacher spread0.215 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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