Investigating laboratory-generated pyrobitumen precursors for unconventional reservoir characterization: a geochemical & petrographic approach.
Bibliographic record
Abstract
rd St NW, Calgary, AB. T2L 2A7 Summary The use of bulk parameters such as the Rock-Eval S2 curve to characterize organic matter in gas shales can lead to the erroneous identification of kerogen (autochthonous; derived from sedimentary organic matter) instead of pyrobitumen (allochthonous, derived from earlier oil charge). Analysis of the pyrobitumen using geochemical and petrological techniques shows that there is wide variation in many of the properties of pyrobitumen as a function of both the precursor oil composition and thermal maturity. It is furthermore believed that many of the properties of pyrobitumens deviate from those of kerogens at similar levels of maturity. This ongoing study aims to characterize some of these properties to provide tools to better identify pyrobitumen and its influence on shale gas reservoir properties.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".