MétaCan
Menu
Back to cohort
Record W3004149697

Recent warming in northwestern Ontario, Canada, inferred from borehole temperature profiles

2001· article· en· W3004149697 on OpenAlexaboutno aff
C. Gosselin, Jean‐Claude Mareschal

Bibliographic record

VenueAGUFM · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsBoreholeGlobal warmingClimate changeEnvironmental scienceClimatologyGeologyPhysical geographyGeographyOceanography
DOInot available

Abstract

fetched live from OpenAlex

[1] We have used the temperature depth profiles available in the region north and northwest of Lake Superior, in Ontario, Canada, to reconstruct the changes in ground surface temperature over the past 500 years. The 49 temperature depth profiles used were obtained for heat flow measurements and are part of two different data sets, one collected around 1980, the other one after 2000. We have discarded 16 of these profiles because of known nonclimatic perturbations (lakes, topography, clear signs of groundwater circulation). We have inverted the remaining 33 profiles to infer the variations in ground surface temperature. Individual and joint inversions consistently show a recent (150– 200 years) warming (1–2 K) of the ground surface. This warming trend is similar to that inferred for northern Manitoba and Saskatchewan, to the northwest, and in eastern Ontario and Quebec, to the southeast. However, there is no clear indication that a cold episode preceded the warming of the past 200 years in northwestern Ontario. The mean increase in ground surface temperature for all boreholes measured between 2000 and 2003 is 1.3 ± 0.8 K compared to 0.8 ± 0.6 K (s) for the 1980 data. This difference suggests that the warming trend is persisting and might even have accelerated recently. Although the longterm trend is climatic, part of the recent warming may be due to deforestation by the logging industry.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.987

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)0.0140.000

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 head0.027
GPT teacher head0.216
Teacher spread0.189 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueAGUFMSame topicClimate change and permafrostFrench-language works237,207