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Old Data, Changed Times, New Resource? A Case Study, Barrytown, New Zealand, Ilmenite Garnet Gold Zircon

2019· article· en· W2984245528 on OpenAlex
Luke Burlet, Graham Lee

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueASEG Extended Abstracts · 2019
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsIlmeniteZirconMineral resource classificationGeologyDatabaseResource (disambiguation)MineralGeochemistryMining engineeringComputer scienceMetallurgyMaterials science

Abstract

fetched live from OpenAlex

SummaryThe project geology has been compiled reviewed and a new, modern, resource database has been developed for the Barrytown New Zealand, Ilmenite Garnet Gold Zircon project.The work required existing databases to be updated to include all historic mineral sands and gold data, and consolidated and checked versus original records.The NZ Petroleum and Minerals (NZPAM) Mineral Report (MR) documents for the Barrytown project were checked and the data was compared to that contained in the project databases compiled prior to this recent 2018 work. Additional information was extracted and added into the databases including omitted holes, collars, size fractions, magnetic fractions, lithology, and especially gold assays. Within the project budget, as much additional data as could possibly be extracted was found by being persistent and systematically working through the contained information. The NZPAM system, although not ideal, does contain a wealth of information.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.255
Teacher spread0.227 · 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