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Record W1603857963 · doi:10.1002/9781118867976.ch6

Flattener #3 – Horizontal Drilling and Fracking

2015· other· en· W1603857963 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDirectional drillingHydraulic fracturingPetroleum engineeringOil shaleDrillingAquiferShale gasTight oilFossil fuelGeologyNatural gasDrilling fluidUnconventional oilMining engineeringEnvironmental scienceGroundwaterEngineeringWaste managementGeotechnical engineeringPaleontology

Abstract

fetched live from OpenAlex

In this chapter, the author reviews and debates some of the main arguments used against shale gas. Offshore drilling, ultra-deep-water, horizontal drilling, and hydraulic fracturing (“fracking”) are game changers for both the natural gas and oil markets, but over the past century the limits have been pushed, facilitating incremental demand growth. Critics argue that fracking may damage drinking water aquifers, but fracking takes place a mile or more below drinking water aquifers and is separated from them by thick layers of impermeable rock. Fracking can be done with water or other liquids. There are also environmental concerns around the water that “comes back” to the surface. The development of US shale gas and tight oil is widely recognized as a major competitive advantage against Europe, Japan, and China. A competitive advantage that may last for a long time, with deep and possible irreversible repercussions.

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 score0.230
Threshold uncertainty score0.769

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.2300.066

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 head0.241
Teacher spread0.228 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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