MétaCan
Menu
Back to cohort

NO STONE UNBURNED: A COMPOSITIONAL ANALYSIS OF OBSIDIAN MICRODEBITAGE BY LASER ABLATION TOF–ICP–MS

2011· article· en· W1575848122 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.

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

Bibliographic record

VenueArchaeometry · 2011
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of Alberta
FundersNational Science Foundation
KeywordsArchaeologyArchaeological scienceLaser ablationSampling (signal processing)Homogeneity (statistics)GeologyArchaeological recordMineralogyMaterials scienceLaserGeographyComputer sciencePhysicsOptics

Abstract

fetched live from OpenAlex

Obsidian is an effective material for the study of prehistoric raw material use and exchange, due to the high degree of homogeneity and redundancy of obsidian materials and manufactured objects in the archaeological record. The destructive nature of many analytical techniques often impedes compositional research because of the damage that may occur to priceless archaeological artefacts. The combination of time‐of‐flight (TOF) ICP–MS with a laser ablation sample introduction system provides a highly efficient means of chemically characterizing obsidian. This study shows that sample size limit capabilities of TOF–ICP–MS analysis of obsidian can reach less than 100 μm. Sampling and analysis of microartefacts enables researchers to overcome problems of sampling bias with very little damage to the valuable existing materials within the archaeological record and expands the potential for chemical compositional analyses in archaeology.

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 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 score0.185
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.220
Teacher spread0.203 · 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