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Record W4253811659 · doi:10.5194/tc-2019-30-rc1

Geodetic glacier mass balance

2019· preprint· en· W4253811659 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsGeodetic datumGlacierBalance (ability)GeodesyGlacier mass balanceGeologyGeographyPhysical geographyMedicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

General comments This paper uses data collected from repeat airborne laser altimetry surveys to determine seasonal mass balance of 6 glaciers in the Columbia and Rocky mountains.Results indicate strong agreement between the geodetic estimations of mass balance and in situ observations.Technically, the paper is quite strong as it includes validation with in situ measurement and a rigorous analysis of the geodetic measurement error, however I found in many cases the writing was unclear (see comments below).In encourage to authors to carefully re-read the manuscript in order to address the many grammatical errors, improper/over use of hyphens and custom terminology throughout.Results from this work however do contribute scientifically to methods and knowledge pertaining to mass balance of Canada's western glaciers of C1 TCD Interactive

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)0.003
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0740.025

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 head0.022
GPT teacher head0.216
Teacher spread0.194 · 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
Published2019
Admission routes1
Has abstractyes

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