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Record W2497639613 · doi:10.1190/1.9781560802197.ch14

Infrared Imaging of Gas-Hydrate-Bearing Cores: State of the Art and Future Prospects

2010· book-chapter· en· W2497639613 on OpenAlex
Philip E. Long, Melanie Holland, Peter Schultheiss, Michael Riedel, Jill L. Weinberger, A. M. Tréhu, Herbert T. Schaef

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociety of Exploration Geophysicists eBooks · 2010
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsPhysicsChemistry

Abstract

fetched live from OpenAlex

Modern digital infrared (IR) thermal imaging of recovered sediment cores is a technical development that opens new scientific opportunities for studying gas-hydrate abundance and texture. Data derived from thermal imaging of gas hydrates provide an entirely new and independent proxy for gas-hydrate abundance in marine sediments. The information on gas-hydrate distribution at the core scale can be used to assess gas-hydrate resources and to constrain the processes resulting in formation of gas hydrate. IR imaging has also become an indispensable guide for sample collection of gas-hydrate and pore water samples. Future development of IR imaging techniques and analyses promises automated estimation of gas-hydrate abundance and characterization of textures immediately after acquiring IR scans of cores.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.726
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.194
Teacher spread0.185 · 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