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Record W2062344118 · doi:10.4236/ajcc.2013.24027

Climate Change Effect on Winter Temperature and Precipitation of Yellowknife, Northwest Territories, Canada from 1943 to 2011

2013· article· en· W2062344118 on OpenAlex
Janelle Laing, Jacqueline Binyamin

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Journal of Climate Change · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsPrecipitationClimatologyNegative correlationPacific decadal oscillationLa NiñaPositive correlationEnvironmental scienceArctic oscillationAtmospheric sciencesEl Niño Southern OscillationNorth Atlantic oscillationGeologyGeographyMeteorology

Abstract

fetched live from OpenAlex

The correlation of the Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), Pacific North American Oscillation (PNA), Arctic Oscillation (AO), and Scandinavia (SCAND) indices with winter (DJF) temperature and precipitation for the period of 1943 to 2011 was analyzed to study climate change and variability of Yellowknife, NWT. SOI correlated negatively with both temperature (r = -0.14) and precipitation (r = -0.06) causing colder, drier conditions during La Nina and warmer, wetter conditions during El Nino. PDO was shown to have a strong positive correlation with both temperature (r = 0.60) and precipitation (r = 0.33) causing warmer, wetter weather in the positive phase and colder, drier weather in the negative phase. PNA showed the strongest positive correlation for both temperature (r = 0.69) and precipitation (r = 0.37) causing very warm and wet conditions in the positive phase and very cold and dry conditions during the negative phase. AO correlated negatively with temperature (r = -0.04) and positively with precipitation (r = 0.24) causing colder, wetter conditions in the positive phase and warmer, drier conditions in the negative phase. Finally SCAND was shown to have a weak negative correlation with both temperature (r = -0.10) and precipitation (r = -0.18). Sunspot area showed a strong negative correlation (r = -0.30) with temperature and a very weak positive correlation (r = 0.07) with total annual precipitation. Yellowknife’s average annual temperature and precipitation has increased by 2.5°C and 120 mm, respectively throughout the past 69 years.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.833

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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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