MétaCan
Menu
← Back to cohort
Record W2981625171 · doi:10.4095/301750

Historical fluctuations of lake shorelines based on geomorphological analysis in the vicinity of Rankin Inlet, Nunavut

2017· report· en· W2981625171 on OpenAlexaffabout
O Bellehumeur-Génier, Greg A. Oldenborger, A -M LeBlanc

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsInletShoreOceanographyGeologyGeomorphologyHydrology (agriculture)GeographyPhysical geographyGeotechnical engineering

Abstract

fetched live from OpenAlex

The purpose of this Open File is to provide information derived from the analysis of lake shorelines in the vicinity of Rankin Inlet, Nunavut. The analysis focused on three areas of interest located north of Rankin Inlet, with different surficial material mosaics. A total of 220 lakes were digitized from air photos and satellite imagery using a geographical information system (GIS) for the period 1954 to 2014. Lake surface areas were computed using the digitized polygons. A visual assessment of the geomorphological dynamics of individual lakes was undertaken to differentiate normal shoreline behavior from that potentially associated with thermokarst. Results showed that lakes in the areas of interest have experienced significant shoreline fluctuation as part of normal lake behavior. Despite the high degree of normal shoreline variability, the geomorphological analysis revealed that certain lakes demonstrated abnormal increases or decreases in area, along with localized shoreline dynamics.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.294
Threshold uncertainty score0.590

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.114
GPT teacher head0.312
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2017
Admission routes2
Has abstractyes

Explore more

Same topicClimate change and permafrost→French-language works237,207→