MétaCan
Menu
Back to cohort
Record W2119324763 · doi:10.5194/cp-12-115-2016

Laurentide Ice Sheet basal temperatures during the last glacial cycle as inferred from borehole data

2016· article· en· W2119324763 on OpenAlexafffundabout
Carolyne Pickler, Hugo Beltrami, J. Mareschal

Bibliographic record

VenueClimate of the past · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsSt. Francis Xavier UniversityUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaAtlantic Canada Opportunities AgencySt. Francis Xavier University
KeywordsGeologyIce sheetGlacial periodIce streamBoreholeIce-sheet modelClimatologyGeomorphologyPaleontologyCryosphereSea ice

Abstract

fetched live from OpenAlex

Thirteen temperature–depth profiles ( ≥ 1500 m) measured in boreholes in eastern and central Canada were inverted to determine the ground surface temperature histories during and after the last glacial cycle. The sites are located in the southern part of the region that was covered by the Laurentide Ice Sheet. The inversions yield ground surface temperatures ranging from −1.4 to 3.0 °C throughout the last glacial cycle. These temperatures, near the pressure melting point of ice, allowed basal flow and fast flowing ice streams at the base of the Laurentide Ice Sheet. Despite such conditions, which have been inferred from geomorphological data, the ice sheet persisted throughout the last glacial cycle. Our results suggest some regional trends in basal temperatures with possible control by internal heat flow.

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 score0.820
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.230
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

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

Citations39
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueClimate of the pastSame topicCryospheric studies and observationsFrench-language works237,207