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Record W4408438622 · doi:10.5194/egusphere-egu25-6364

The double emergence of TCRE

2025· preprint· en· W4408438622 on OpenAlexaff
Andrew H. MacDougall, Alexander MacIsaac

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicEarth Systems and Cosmic Evolution
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsComputer sciencePsychology

Abstract

fetched live from OpenAlex

The TCRE relationship underlies the necessity of net zero emissions for climate stabilization and the utility of carbon budgets as a policy tool. TCRE emerges near universally from Earth system models, and is consistent with observations. However, recent work has systematically dismantled the leading hypothesis explaining the phenomenon, concluding “that this proportionality is not amenable to a simple physical explanation, but rather arises because of the complex interplay of multiple physical and biogeochemical processes.'' (Gillett, 2023). Here we set two intermediate complexity Earth system models (EMICs) to abiotic states, then turn on broad components of Earth's biogeochemical cycles one at a time to see which combination of processes cause TCRE to emerge.We find that TCRE emerges when ocean alkalinity is set to observed values, without life on land. TCRE likewise emerges independently when the terrestrial biosphere is turned on, with the ocean in an abiotic low alkalinity state. Idealized experiments with the EMICs show that TCRE occurs for configurations of the Earth system where characteristic timescales of carbon absorption and heat absorption are nearly the same. Our results suggest that the emergence of TCRE does in-fact rely on a simple physical mechanism, but why the living components of Earth system are matching the characteristic timescale of carbon absorption to that of heat remains mysterious.Gillett, N.P.: Warming proportional to cumulative carbon emissions not explained by heat and carbon sharing mixing processes. Nature Communications 14(1), 6466 (2023)

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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