MétaCan
Menu
Back to cohort
Record W2045486079 · doi:10.1144/sp384.12

Ground penetrating radar use in three contrasting soil textures in southern Ontario

2013· article· en· W2045486079 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeological Society London Special Publications · 2013
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsTrent UniversityOntario Tech University
Fundersnot available
KeywordsGround-penetrating radarGeologyRadarRemote sensingEngineering

Abstract

fetched live from OpenAlex

Abstract Ground penetrating radar (GPR) is a non-invasive, geophysical tool that can be used for the identification of clandestine graves. GPR operates by detecting density differences in soil by the transmission of high frequency electromagnetic waves from an antenna. Domestic pig ( Sus scrofa domesticus ) carcasses were clothed in 100% cotton t-shirts and 50% cotton/50% polyester briefs, and buried at a consistent depth at three field sites of contrasting soil texture (silty clay loam, fine sand and fine sandy loam) in southern Ontario. GPR was used to detect and monitor the graves for a period of 14 months post-burial. Analysis of collected data revealed that GPR had applicability in the identification of clandestine graves in silty clay loam and fine sandy loam soils, but was not suitable for detection in the fine sandy soil studied. The results of this research have applicability within forensic investigations involving decomposing remains by aiding in the location of clandestine graves in loam soils in southern Ontario through the use of GPR.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.231
Teacher spread0.202 · 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