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Record W4224247205 · doi:10.5194/npg-2022-2-ac1

Comment on npg-2022-2

2022· peer-review· en· W4224247205 on OpenAlexaff
Allan R. Willms

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBistabilityArcticAtmosphere (unit)Carbon dioxideAtmospheric sciencesEnvironmental scienceFlux (metallurgy)Carbon fibersRepresentative Concentration PathwaysClimate modelThermodynamicsMechanicsPhysicsChemistryMaterials scienceClimate changeOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract. A column model of the Arctic atmosphere is developed including the nonlinear positive feedback responses of surface albedo and water vapour to temperature. The atmosphere is treated as a grey gas and the flux of longwave radiation is governed by the two-stream Schwarzschild equations. Water vapour concentration is determined by the Clausius–Clapeyron equation. Representative concentration pathways (RCPs) are used to model carbon dioxide concentrations into the future. The resulting 9D two-point boundary value problem is solved under various RCPs and the solutions analysed. The model predicts that under the highest carbon pathway, the Arctic climate will undergo an irreversible bifurcation to a warm steady state, which would correspond to annually ice-free conditions. Under the lowest carbon pathway, corresponding to very aggressive carbon emission reductions, the model exhibits only a mild increase in Arctic temperatures. Under the two intermediate carbon pathways, temperatures increase more substantially, and the system enters a region of bistability where external perturbations could possibly cause an irreversible switch to a warm, ice-free state.

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)0.003
metaresearch head score (Gemma)0.022
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: Commentary · Consensus signal: none
Teacher disagreement score0.176
Threshold uncertainty score0.590

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0230.011
Insufficient payload (model declined to judge)0.1760.138

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 head0.014
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
GenreCommentary

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
Published2022
Admission routes1
Has abstractyes

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