MétaCan
Menu
Back to cohort
Record W2125056828 · doi:10.1175/jcli4025.1

Ice Bridges on the St. Lawrence River as an Index of Winter Severity from 1620 to 1910

2007· article· en· W2125056828 on OpenAlexaffabout
Daniel Houle, Jean‐David Moore, Jean Provencher

Bibliographic record

VenueJournal of Climate · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)
FundersObservatoire de Paris, Université de Recherche Paris Sciences et Lettres
KeywordsClimatologyNorthern HemisphereLittle ice agePeriod (music)Climate changeIce coreEnvironmental sciencePhysical geographyGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

Abstract Temperature reconstruction of the last thousand years suggests that an unprecedented warming (+0.6°C) occurred over the globe in the last century. However, regional variations in climate are not resolved by Northern Hemisphere reconstructions. In northeastern North America, past climate and, particularly, past winter variations are poorly known. Here, the authors report on the variation of a winter temperature index during the 1620–1910 period, based on the ice bridge formation (IBF) rate on the Saint Lawrence River at Québec City (Canada), combined with instrumental data (1876–2000). During this 300-yr period, the IBF rate shows that winters in the seventeenth and eighteenth centuries were warmer than those in the nineteenth century. In particular, the IBF rate suggests that winter severity culminated in the 1850–1900 period, while very few ice bridges were reported between 1620 and 1740, presumably because of warmer temperatures and the relative scarcity of historical documents for the 1680–1740 period. These data suggest that winter temperature, particularly between ∼1800 and 1910, was 2.4° to 4.0°C colder than the last 30-yr average. Major volcanic eruptions had a significant positive impact on IBF rates, which is consistent with their role as important climate-forcing events.

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 score0.030
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
Bibliometrics0.0000.000
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 head0.271
Teacher spread0.250 · 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
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueJournal of ClimateSame topicTree-ring climate responsesFrench-language works237,207