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Record W1977304079 · doi:10.3189/172756407782871431

River-ice break-up/freeze-up: a review of climatic drivers, historical trends and future predictions

2007· review· en· W1977304079 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnals of Glaciology · 2007
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of VictoriaEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClimatologyTeleconnectionFlood mythClimate changeLead (geology)Environmental sciencePhysical geographyGeologyGeographyEl Niño Southern OscillationOceanography

Abstract

fetched live from OpenAlex

Abstract River ice plays a fundamental role in biological, chemical and physical processes that control freshwater regimes of the cold regions. Moreover, it can have enormous economic implications for river-based developments. All such activities and processes can be modified significantly by any changes to river-ice thickness, composition or event timing and severity. This paper briefly reviews some of the major hydraulic, mechanical and thermodynamic processes controlling river-ice events and how these are influenced by variations in climate. A regional and temporal synthesis is also made of the observed historical trends in river-ice break-up/freeze-up occurrence from the Eurasian and North American cold regions. This involves assessment of several hydroclimatic variables that have influenced past trends and variability in river-ice break-up/freeze-up dates including air-temperature indicators (e.g. seasonal temperature, 0˚C isotherm dates and various degree-days) and large-scale atmospheric circulation patterns or teleconnections. Implications of future climate change on the timing and severity of river-ice events are presented and discussed in relation to the historical trends. Attention is drawn to the increasing trends towards the occurrence of mid-winter break-up events that can produce especially severe flood conditions but prove to be the most difficult type of event to model and predict.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.068
GPT teacher head0.331
Teacher spread0.264 · 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