MétaCan
Menu
Back to cohort
Record W2077194008 · doi:10.1109/tip.2011.2164418

HANS: Controlling Ink-Jet Print Attributes Via Neugebauer Primary Area Coverages

2011· article· en· W2077194008 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Image Processing · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsHewlett-Packard (Canada)
Fundersnot available
KeywordsGamutHalftoneInkwellSubtractive colorColor spaceComputer scienceDigital printingComputer graphics (images)Artificial intelligenceComputer visionOpticsEngineering drawingEngineeringPhysicsImage (mathematics)

Abstract

fetched live from OpenAlex

Ink-jet print attributes such as color gamut, grain, and cost are consequences of the materials and printing technology used and of choices made during color management, color separation, and halftoning operation. Traditionally, color separation determines what amounts of the available inks to use for each reproducible color, and halftoning deals with the spatial distribution of inks that also results in the nature of their overprinting. However, using an ink space as a means of communication between color separation and halftoning gives access only to some of the printed patterns that a printing system is capable of and, therefore, only to a reduced range of print attributes. Here, a method, i.e., Halftone Area Neugebauer Separation, is proposed to gain access to all possible printable patterns by specifying relative area coverages of a printing system's Neugebauer primaries instead of only ink amounts. This results in delivering prints with more optimal attributes (e.g., using less ink and giving rise to a larger color gamut) than is possible using current methods.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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