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Record W4313061300 · doi:10.13031/ja.14853

Exceedance Probability Model for Predicting the Frequency of Frost-Free Days

2022· article· en· W4313061300 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of the ASABE · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsFrost (temperature)Range (aeronautics)LatitudeEnvironmental scienceClimatologyStatisticsMathematicsMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Highlights Number of frost-free days (FFD) increased exponentially with an increase in winter daily minimum temperatures. Winter daily minimum temperatures increased at a rate of 2°C per 100 years for the investigated stations. Stations situated in southern Canada are more susceptible to increase in winter FFD. The developed simple model can be used to reliably forecast FFD and other temperature related variables. Abstract. Data collected between 1940 and 2009 from 11 weather stations across central Canada were used to explore temporal changes in mean winter daily minimum temperatures (WDMT) and the number of frost-free days (FFD) per winter. The main objective of the study was to estimate and predict temporal trends in FFD per winter, as well as to investigate the relationship between FFD and mean (WDMT) across a wide range of latitudes in central Canada. An exceedance probability model was developed to predict FFD per winter based on the definition of FFD per winter as an exceedance variable, the normal distribution function as an approximation of the frequency distribution of WDMT, and a relationship between the standard deviations and means of WDMT. The analyses of the mean WDMT time series revealed an overall average temperature increase of about 2°C over 100 years for the investigated stations. Further, the stations in central Canada have experienced an increase in FFD, with an average increase of 12 days in 100 years. The rate of increase in FFD, however, varied considerably among the 11 stations, from approximately 0.6 to 36 days per 100 years. Stations situated at northern latitudes exhibited relatively small increases, or no increases in FFD per winter, as compared to stations situated in southern areas. The FFD per winter were found to increase exponentially with steady increases in the mean WDMT values, matching the results obtained by solution of the developed exceedance model. Therefore, the exceedance model was shown to be an excellent tool for predicting FFD per winter, at least for the stations located widely across central Canada. Keywords: Climate change, Exceedance probability model, Frost free days, Minimum daily temperature.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.001
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 head0.036
GPT teacher head0.244
Teacher spread0.208 · 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