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Record W6947938282 · doi:10.4224/40000413

A brief review of the numerical modelling of ice jam flooding and studies relevant to coastal communities of Ontario's Far North

2018· report· en· W6947938282 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2018
Typereport
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsNational Research Council CanadaGovernment of Canada
Fundersnot available
KeywordsFlooding (psychology)ShoreNumerical modelsBayChristian ministryNumerical modeling

Abstract

fetched live from OpenAlex

Coastal communities of Ontario’s Far North located near the shores of James and Hudson Bay are prone to ice jam flooding. The ability to forecast flooding is required for effective and optimized emergency planning and the reduction of threats and costs. The present report is a brief review of numerical modelling approaches, available tools, required data and supporting technologies and methods for the development of modelling and forecasting tools. The report also provides a summary of available studies about numerical modelling of ice jam flooding concerning Ontario’ Far North based on a review of open literature. The report also provides recommendations for the Surface Water Monitoring Centre of Ontario Ministry of Natural Resources and Forestry on next steps towards developing such model and forecast tool developments.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.202
GPT teacher head0.355
Teacher spread0.153 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2018
Admission routes3
Has abstractyes

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