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Record W6987476817

Styleform IT v. Facebook

2018· article· en· W6987476817 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsnot available
Fundersnot available
KeywordsExtortionOrder (exchange)RevenueSocial mediaOfficerQuarter (Canadian coin)PseudonymField (mathematics)Payment
DOInot available

Abstract

fetched live from OpenAlex

There may be a court form that you can use for your response.You can find these court forms and more information at the California Courts Online Self-Help Center (www.courtinfo.ca.gov/se/fhelp), your county law library, or the courthouse nearest you.If you cannot pay the filing fee, ask the court clerk for a fee waiver form.If you do not file your response on time, you may lose the case by default, and your wages, money, and property may be taken without further warning from the court.There are other legal requirements.You may want to call an attorney right away.If you do not know an attorney, you may want to call an attorney referral service.If you cannot afford an attorney, you may be eligible for free legal services from a nonprofit legal services program.You can locale these nonprofit groups at the California Legal Services Web site

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)0.008
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: Other
Teacher disagreement score0.054
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0540.013

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 head0.067
GPT teacher head0.359
Teacher spread0.292 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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Same topicIntellectual Property LawFrench-language works237,207