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Record W2302431251 · doi:10.11575/prism/9484

Critical Issues in Gambling Research: Alberta Gambling Research Institute's 14th Annual Conference

2015· article· en· W2302431251 on OpenAlexaboutno aff
Jennifer N. Arthur, Yale D. Belanger, Emma Casey, Darren R. Christensen, Luke Clark, Shawn R. Currie, Paul Delfabbro, Mike J. Dixon, Kevin Harrigan, Haifang Huang, Bonnie Lee, Carrie A. Leonard, Daniel S. McGrath, Keis Ohtsuka, Jonathan Parke, Garry J. Smith, Claudia Steinke, Rachel A. Volberg, Gordon Walker, Catharine A. Winstanley, Richard T. A. Wood

Bibliographic record

VenueOpen MIND · 2015
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceLibrary scienceCriminologyPsychologySociology

Abstract

fetched live from OpenAlex

The Alberta Gambling Research Institute and the University of Lethbridge co-sponsored the fourteenth in a series of special interest conferences in the area of gambling studies. The conference theme was "Critical Issues in Gambling Research." The conference took place Friday, March 27, & Saturday, March 28, 2015 at the Banff Centre.

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)0.071
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.868
Threshold uncertainty score0.375

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0710.031
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.004
Science and technology studies0.0130.011
Scholarly communication0.0170.004
Open science0.0060.010
Research integrity0.0170.024
Insufficient payload (model declined to judge)0.0100.002

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 head0.804
GPT teacher head0.646
Teacher spread0.158 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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