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Record W4403276747 · doi:10.1126/sciadv.adq4893

Temperature sensitivity of the mineral permafrost feedback at the continental scale

2024· article· en· W4403276747 on OpenAlexaff
E. Walsh, Robert Hilton, Suzanne E. Tank, Edwin Amos

Bibliographic record

VenueScience Advances · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsAurora CollegeUniversity of Alberta
Fundersnot available
KeywordsPermafrostScale (ratio)Sensitivity (control systems)MineralMineral explorationEarth scienceGeologyEnvironmental sciencePhysical geographyOceanographyGeochemistryEcologyGeographyBiologyCartographyEngineering

Abstract

fetched live from OpenAlex

Oxidative weathering of sulfide minerals in sedimentary rocks releases carbon dioxide (CO 2 ) into the atmosphere. In permafrost zones, this could be a positive feedback on climate change if it increases with warming, yet sulfide oxidation rates and their temperature response remain unknown over large spatial and temporal scales. We analyze a 60-year sulfate concentration dataset from catchments across the Mackenzie River Basin. Sulfate fluxes increased by 45% in the mainstem with 2.3°C of warming, and the temperature sensitivity suggests that continental-scale CO 2 fluxes could double by 2100. The largest increases occur in catchments with geomorphic settings which act to rapidly expose rocks through physical weathering and thermokarst processes. Comparisons with a weathering model suggest that warming can increase reaction rates, and changes in the exposure of minerals with warming are also required. Future warming across vast Arctic landscapes could further increase sulfide oxidation rates and affect regional carbon cycle budgets.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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 teacher head, not a consensus.

Study designObservational
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

Citations16
Published2024
Admission routes1
Has abstractyes

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