MétaCan
Menu
Back to cohort
Record W4288053335 · doi:10.3390/s22155568

Correction: Elsheikh et al. Low-Cost Real-Time PPP/INS Integration for Automated Land Vehicles. Sensors 2019, 19, 4896

2022· erratum· en· W4288053335 on OpenAlexafffund
Mohamed Elsheikh, Walid Abdelfatah, Aboelmagd Noureldin, Umar Iqbal, Michael J. Korenberg

Bibliographic record

VenueSensors · 2022
Typeerratum
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsRoyal Military College of CanadaTrusted Positioning (Canada)Queen's University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsComputer scienceReal-time computing

Abstract

fetched live from OpenAlex

The authors wish to make the following corrections in the original paper [...].

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)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.053
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0040.002
Scholarly communication0.0050.003
Open science0.0030.003
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0630.067

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 head0.009
GPT teacher head0.246
Teacher spread0.236 · 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 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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueSensorsSame topicGNSS positioning and interferenceFrench-language works237,207