MétaCan
Menu
Back to cohort
Record W2982244038 · doi:10.4095/224966

Surficial geology, June Lake, British Columbia

2008· report· en· W2982244038 on OpenAlexaffabout
J M Bednarski

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyArchaeologyOceanographyPhysical geographyHydrology (agriculture)GeochemistryGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

The surficial geology of the June Lake (NTS 94 P/16) map area is dominated by the effects of continental glaciation during the Late Wisconsinan stage (ca. 25 000-10 000 years ago). In general the ice sheet advanced from the northeast, but as the ice thinned during deglaciation, the flow emanated from the Mackenzie River valley from the north-northwest. This ice flow was caused by a lobe in the ice sheet that filled a broad lowland, centered down the east half of the map area. The central axis of the lowland is occupied by a large meltwater channel in which Thinahtea Creek, and a string of small lakes, currently lie. Several eskers also run along the channel floor, which suggest that the channel may have initially formed as a subglacial tunnel. The lobate pattern of the ice margin is marked by numerous small ridges of till, which form nested arcuate patterns. The ridges are thought to be either end moraine segments or crevasse fillings and their arcuate is thought to show the progressive retreat of the ice margin to the northwest, when considered with the nested pattern of meltwater channels. Much of the map area is underlain by thick clayey till, which is poorly drained and covered by extensive muskeg, which forms hummocky peatlands. Areas of thick peat are likely underlain by permafrost and probably contain significant amounts of ground ice.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.277
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.1150.001

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 head0.033
GPT teacher head0.223
Teacher spread0.191 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2008
Admission routes2
Has abstractyes

Explore more

Same topicGeological Modeling and AnalysisFrench-language works237,207