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Record W4416291635 · doi:10.29173/alr2879

The Pore Space Race: Conflicts of Subsurface Rights in the Age of Carbon Capture and Sequestration

2025· article· W4416291635 on OpenAlexvenueaboutno aff
Nick Ettinger, Tyson Dyck, A. Wiberg

Bibliographic record

VenueAlberta Law Review · 2025
Typearticle
Language
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsStatutory lawSpace (punctuation)Characterisation of pore space in soilSoftware deploymentCarbon sequestrationCarbon capture and storage (timeline)Focus (optics)

Abstract

fetched live from OpenAlex

As carbon capture and sequestration expands to meet climate goals, conflicts of subsurface rights present a significant obstacle. This article examines the ownership and regulation of pore space across Canada and the United States. It analyzes divergent common law and statutory frameworks governing pore space ownership and the management of convergent subsurface rights across various jurisdictions, with a particular focus on Alberta. The authors demonstrate how fragmented subsurface rights create legal uncertainty and assess legal mechanisms for mitigating these conflicts to enable the responsible deployment ofcarbon capture and sequestration.

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)0.005
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.884

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.020
Scholarly communication0.0070.005
Open science0.0020.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.278
Teacher spread0.265 · 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
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
Published2025
Admission routes2
Has abstractyes

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