MétaCan
Menu
Back to cohort
Record W6910998710 · doi:10.5066/p95oktu7

Whole rock geochemical data from the eastern part of the Yukon-Tanana Upland region, Alaska, USA

2021· dataset· en· W6910998710 on OpenAlexaboutno aff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsGeochronologyTrace elementIntrusionIgneous rock

Abstract

fetched live from OpenAlex

This data release is part of a 2016-2019 study on the geology, geochemistry and geochronology of ore systems in the eastern Yukon-Tanana Upland region, Alaska. Whole rock chemistry was conducted on 185 samples, mostly from Au prospects, with lesser samples from porphyry Cu prospects. Geographically, most samples are from gold prospects near the Pogo Au mine and east to Black Mountain in the Big Delta quadrangle. Fewer samples are from prospects in the Eagle and Tanacross Quadrangles. Samples were submitted to the USGS contract laboratory and analyzed for select trace elements and gold. Sixty elements were determined by inductively coupled plasma-optical emission spectroscopy-mass spectroscopy (ICP-OES-MS), sodium peroxide fusion (ICP-60). Gold was determined by lead fusion fire assay.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.184
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.009
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.018

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 head0.040
GPT teacher head0.233
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueUSGS DOI Tool Production EnvironmentFrench-language works237,207