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Record W6981809888

First joint SPE/DOE symposium on enhanced oil recovery, proceedings supplement

2014· other· en· W6981809888 on OpenAlexaboutno aff

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIncentivePetroleumGovernment (linguistics)Session (web analytics)Petroleum industryJoint (building)
DOInot available

Abstract

fetched live from OpenAlex

The First Joint Symposium on Enhanced Oil Recovery sponsored by the Society of Petroleum Engineers and the US Department of Energy was held in Tulsa, Oklahoma. Besides the thirty-three technical papers which covered all phases of enhanced oil recovery and were published in the Proceedings, the Symposium included a session on Enhanced Oil Recovery Incentives where ten papers were presented which discussed the status of enhanced oil recovery technology, and included papers on incentive programs of the United States, Canada and Venezuela. These papers are published in this Proceedings Supplement under the following titles: Federal Government Role in enhanced Oil Recovery; Financial Realities of an Adequate Petroleum Supply; Major Technology Constraints in Enhanced Oil Recovery; Decontrol-Opportunities and Dangers; Status of EOR Technology; Impact of Federal Incentives on US Production; Canadian Incentives Program; and Heavy Oil Incentives in Venezuela.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.118
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1180.039

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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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