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Record W4230973511 · doi:10.32628/ijsrst18401164

Aquamarine Gemstone

2018· article· en· W4230973511 on OpenAlexaboutno aff
Nazia Sultana, Sankara Pitchaiah Podila

Bibliographic record

VenueInternational Journal of Scientific Research in Science and Technology · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMineralogy and Gemology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaGeographyMineralogyAncient historyArchaeologyGeologyHistory

Abstract

fetched live from OpenAlex

Aquamarine gemstone is one of the Beryl mineral varieties with Beryllium aluminium silicate composition. Its bluish green color caused from Fe2+ions puts it as a special variety. It is used in jewellery and has some industrial applications. This beautiful gemstone is reported from few countries only, namely India, Brazil, Canada, China, Italy, Pakistan, Russia, Ethiopia, Madagascar, Mozambique, Namibia, Nigeria, United Kingdom, United States, Mexico and Vietnam. The present study collected its occurrences from various parts of the world and studied the variation of oxides analyzed from Aquamarine. It is observed that SiO2 ranges from 64.99% to 72.48%, Al2O3:11.63% to 19.91%; BeO: 12.9% to 13.79%; FeO: 0.11% to 5.03%; CaO:0.01 %to 0.83%;MgO:0.00% to 1.93%; Na2O:0.10% to 3.53%; K2O:nearly zero to 3.31% and MnO:0.00% to 0.06%.

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 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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.013
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.066
GPT teacher head0.387
Teacher spread0.321 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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