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Record W4396974951 · doi:10.1071/ep23048

Source rocks of the Birrindudu Basin: perspectives from a new sampling program

2024· article· en· W4396974951 on OpenAlexaff
Grace Butcher, Emmanuelle Grosjean, Tehani Palu, Padmasiri Ranasinghe, Richard Kempton, Siyumini Perera

Bibliographic record

VenueAustralian Energy Producers journal. · 2024
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsKensington Health
Fundersnot available
KeywordsStructural basinGeologySampling (signal processing)Source rockGeochemistryArchaeologyPaleontologyGeographyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The Paleo- to Mesoproterozoic Birrindudu Basin is an underexplored frontier basin straddling the Northern Territory and Western Australia, and is a region of focus for the second phase of Geoscience Australia’s Exploring for the Future (EFTF) program (2020–2024). Hydrocarbon exploration in the Birrindudu Basin has been limited and a thorough assessment of the basin’s petroleum potential is lacking due to the absence of data in the region. To bridge this data gap, a comprehensive analytical program including organic petrology, programmed pyrolysis and oil fluid inclusion analysis was undertaken on cores from six drill holes to improve the understanding of the basin’s source rock potential and assess petroleum migration. Organic petrological analyses reveal that the primary maceral identified in the cores is alginite mainly originating from filamentous cyanobacteria, while bitumen is the most common unstructured secondary organic matter. New reflectance data based on alginite and bitumen reflectance indicate the sampled sections have reached a thermal maturity suitable for hydrocarbon generation. Oil inclusion analyses provide evidence for oil generation and migration, and hence elements of a petroleum system are present in the basin.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.557

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.257
Teacher spread0.234 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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