MétaCan
Menu
Back to cohort

Diet and Trace Elements

2018· other· en· W4230398419 on OpenAlexaff
Alexis E. Dolphin

Bibliographic record

VenueThe Encyclopedia of Archaeological Sciences · 2018
Typeother
Languageen
FieldChemistry
TopicHeavy Metals in Plants
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTRACE (psycholinguistics)Meaning (existential)Trace elementIdentity (music)Variation (astronomy)Trace fossilElement (criminal law)BiologyEpistemologyAestheticsGeologyPaleontologyArtPhilosophyLinguisticsPolitical scienceGeochemistry

Abstract

fetched live from OpenAlex

Trace element analyses of human bones and teeth are used to reconstruct the diets of ancient peoples. Trace elements from soils and water are absorbed by plants and animals, and are then passed along to humans whenever they eat or drink. The incorporation of these elements into bodily tissues allows researchers to comment upon the environments in which past peoples lived, the resources available to them, and the meaning of inter‐ and intragroup variation for understanding cultural change, inequality, identity, and belief systems.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.027
GPT teacher head0.291
Teacher spread0.265 · 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
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe Encyclopedia of Archaeological SciencesSame topicHeavy Metals in PlantsFrench-language works237,207