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Record W33601243 · doi:10.1016/j.nedt.2020.104740

A Short Note on Discrete Representability of Independence Models.

2006· article· en· W33601243 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProbabilistic Graphical Models · 2006
Typearticle
Languageen
FieldComputer Science
TopicBayesian Modeling and Causal Inference
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsIndependence (probability theory)Computer scienceTheoretical computer scienceMathematical economicsEconometricsMathematicsStatistics

Abstract

fetched live from OpenAlex

The prevalence of bullying in nursing and nursing education is of serious concern. Not only is bullying an issue at the interpersonal level, it is also pervasive at structural and institutional levels. Addressing bullying requires attention to all levels. In previous published work, we emphasized the importance of transparent and easily accessible processes and reporting mechanisms for students if or when they witness or experience bullying in nursing education. In this paper, we describe one of a number of education initiatives designed to inform stakeholders (students, faculty members, clinical instructors, registered nurses, clinical education leaders) about the prevalence of bullying, the nature of bullying, the consequences of bullying, and some strategies to address bullying in nursing education. We chose a creative approach in the form of a graphic novella (aka comic) because we believed that this medium would be visually appealing and user friendly and would therefore draw stakeholders, especially students, to the sensitive nature of the content embedded within it.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.276
Teacher spread0.241 · 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