MétaCan
Menu
Back to cohort
Record W2150322778 · doi:10.4095/223024

Production of a residual gravity anomaly map for Gaspésie (northern Appalachian Mountains), Quebec, by a graphical method

2006· report· en· W2150322778 on OpenAlexaffabout
Nicolas Pinet, Pierre Keating, P Brouillette, Denis Lavoie

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsResidualCartographyGravity anomalyAnomaly (physics)GeologyBouguer anomalyPhysical geographyGeographyGeodesyComputer sciencePaleontologyAlgorithmPhysics

Abstract

fetched live from OpenAlex

The authors present a residual gravity map for Gaspésie based on a separation of the regional and residual fields by a graphical method. This map results from the smoothing of 24 gravity profiles with lengths that far exceed the dimension of the zone of interest. The base value of the regional field has been estimated by taking into account surface data and by calculating the maximum gravity lows associated with relatively low-density Silurian-Devonian rocks. The residual gravity map includes all the gravity features that are clearly associated with shallow sources and shows a minimum distortion of the shape of the anomalies.

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)0.002
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.471
Threshold uncertainty score0.948

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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

Citations7
Published2006
Admission routes2
Has abstractyes

Explore more

Same topicGeophysical and Geoelectrical MethodsFrench-language works237,207