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Heat flow of the eastern Canadian rifted continental margin revisited

2007· article· en· W1967240455 on OpenAlexaboutno aff
Bruno Goutorbe, Laureen Drab, Nicolas Loubet, Francis Lucazeau

Bibliographic record

VenueTerra Nova · 2007
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyContinental marginHeat flowNova scotiaAsymmetryThermal conductivityHomogeneousFlow (mathematics)Mantle (geology)Margin (machine learning)ThermalPaleontologyOceanographyMechanicsMeteorologyTectonicsThermodynamicsGeography

Abstract

fetched live from OpenAlex

Abstract Continental shelves are regions where heat flow is not measured directly by conventional marine techniques, but estimated from oil exploration data with possible bias. In order to overcome this problem, we recently proposed a method based on neural networks (Geophys J Int 2006, 166:115) that provides better constraints on thermal conductivity: it allowed us to derive 161 heat flow estimates on the eastern margin of Canada, where previous studies had concluded to the existence of heat flow higher than that in the adjacent continent and ocean. We conversely found rather homogeneous values (∼45–55 mW m−2) all along and across the margins, from Labrador to Nova Scotia. The difference seems essentially related to the porosity of sediments that was not taken into account in previous studies. Our results support a high asymmetry for the conjugate Iberian‐Canadian margins, and could indicate that mantle heat flow increases abruptly from the Canadian shield to the margins.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2007
Admission routes1
Has abstractyes

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