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Record W4394779749

Development of an ion microprobe technique for the in situ isotopic analysis of organic carbon - Application of the origin of bitumens associated with uranium deposits in the Athabasca (Canada) and Witwatersrand (South Africa)

2004· preprint· fr· W4394779749 on OpenAlexaboutno aff
Laure Sangély

Bibliographic record

VenueOpenGrey (Institut de l'Information Scientifique et Technique) · 2004
Typepreprint
Languagefr
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMicroprobeUraniumIn situCarbon fibersGeologyMineralogyGeochemistryChemistryEnvironmental chemistryMetallurgyMaterials scienceOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Des mesures de [Delta]13C par sonde ionique ont été effectuées dans des bitumes provenant des gisements d'uranium de l'Athabasca et du Witwatersrand. Les variations de la proportion en groupements aliphatiques ont été mesurées par micro spectroscopie infrarouge à transformée de Fourier. Une corrélation positive est observée entre la teneur en groupements aliphatiques et les valeurs de [Delta]13C détenninées à l'échelle micrométrique pour l'ensemble des bitumes analysés. Les fractionnements isotopiques du carbone observés lors d'expériences de synthèse abiogénique d'hydrocarbures entre le carbone inorganique et les différentes classes de composés produits pourraient expliquer à la fois la gamme des valeurs de [Delta]13C et leur corrélation avec la teneur en groupements aliphatiques. Cette hypothèse semble en accord avec la présence de CO2 et H2 dans la phase gazeuse des inclusions fluides associées aux deux gisements, qui pourraient avoir joué le rôle de réactifs lors de la synthèse des hydrocarbures.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.995
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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 designBench or experimental
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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

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