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Record W4411100376 · doi:10.1007/978-3-031-91578-9_1

Electron microscopy image showing a detailed view of a surface with a textured, uneven pattern. The image highlights the fine structural details and variations in the surface morphology, typical of high-resolution electron microscopy. The grayscale tones emphasize the contrast between different areas, revealing intricate features and potential material composition differences. AirLetters A simple black and white symbol depicting a hand with three horizontal lines extending from the palm, representing a gesture or motion. The design is minimalistic and stylized. : An Open Vide A blue and white road sign with a red border, featuring a symbol of a bridge. The bridge icon is depicted in light blue against a white background, enclosed within a circular red border. The sign indicates the presence of a bridge or overpass. Dataset of Characters Drawn in the Air

2025· book-chapter· en· W4411100376 on OpenAlexaff
Rishit Dagli, Guillaume Berger, Joanna Materzyńska, Ingo Bax, Roland Memisevic

Bibliographic record

VenueLecture notes in computer science · 2025
Typebook-chapter
Languageen
FieldComputer Science
TopicHand Gesture Recognition Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSurface (topology)Resolution (logic)Morphology (biology)Computer scienceImage (mathematics)Mathematical morphologyElectron microscopeHigh resolutionComputer visionArtificial intelligenceMicroscopyImage formationComputer graphics (images)OpticsImage processingMaterials sciencePhysicsGeometryGeologyMathematicsRemote sensing

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0470.011

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 head0.015
GPT teacher head0.271
Teacher spread0.256 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

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