MétaCan
Menu
Back to cohort
Record W4413141550 · doi:10.1007/s43762-025-00202-z

Correction: Advancing translational human dynamics research: bridging space, mind, and computational urban science in the era of GeoAI

2025· article· en· W4413141550 on OpenAlexaff
Bin Jiang, Tao Cheng, Ming‐Hsiang Tsou, Di Zhu, Xinyue Ye

Bibliographic record

VenueComputational Urban Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsBridging (networking)Space (punctuation)Dynamics (music)Data scienceTranslational scienceComputer scienceCognitive scienceSociologyPsychologySocial science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.008
metaresearch head score (Gemma)0.211
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 score0.131
Threshold uncertainty score0.438

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.211
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0060.006
Science and technology studies0.0060.006
Scholarly communication0.0080.005
Open science0.0070.005
Research integrity0.0170.021
Insufficient payload (model declined to judge)0.1310.057

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 head0.026
GPT teacher head0.333
Teacher spread0.307 · 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

Citations0
Published2025
Admission routes1
Has abstractno

Explore more

Same venueComputational Urban ScienceSame topicHealth, Environment, Cognitive AgingFrench-language works237,207