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Record W7112365630

Canadian Industrial Design Patent No. 195351 (Face Shield)

2021· other· en· W7112365630 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of the Arts London Research Online (University of the Arts London) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsShieldGuard (computer science)Face (sociological concept)Face shieldPlan (archaeology)Representation (politics)
DOInot available

Abstract

fetched live from OpenAlex

National Application/Registration : 195351 Date of Registration : 2021-10-21 Made available on : 2021-10-21 Status : Registered Title or finished article: FACE SHIELD Canadian Classification: 29-02-DEVICES AND EQUIPMENT FOR ACCIDENT PREVENTION AND FOR RESCUE, NOT ELSEWHERE SPECIFIED Description: N/A Statement: The design is the features of shape and configuration of the FACE SHIELD shown in the representation. The portions shown in broken lines in FIG. 1 illustrating a human figure show environment and do not form part of the design. The application includes a representation of the design in which: FIG.1 is a perspective view of the FACE SHIELD in accordance with said Industrial Design, shown in use; FIG. 2 is a front view of the FACE SHIELD of FIG. 1; FIG. 3 is a left side view of the FACE SHIELD of FIG. 1; FIG. 4 is a top plan view of the FACE SHIELD of FIG. 1; FIG. 5 is a right side view of the FACE SHIELD of FIG. 1; FIG. 6 is a rear view of the FACE SHIELD of FIG. 1; FIG. 7 is a bottom plan view of the FACE SHIELD of FIG. 1; and FIG. 8 is a front view of the guard portion of the FACE SHIELD shown in an unfolded position UX Design and Research, User Testing, Visualisation

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)0.001
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.762
Threshold uncertainty score0.647

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.5460.292

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 head0.136
GPT teacher head0.273
Teacher spread0.137 · 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
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
Published2021
Admission routes1
Has abstractyes

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Same venueUniversity of the Arts London Research Online (University of the Arts London)French-language works237,207