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Record W4400991670 · doi:10.69554/cvhz4988

Making the save: How 40 hockey players funded a new clinical trial (and the team that made it happen)

2023· article· en· W4400991670 on OpenAlexaffabout
Michael Siebert, Brooke Rose

Bibliographic record

VenueJournal of education advancement & marketing. · 2023
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIce hockeyAeronauticsPsychologyApplied psychologyPhysical medicine and rehabilitationMedicineEngineering

Abstract

fetched live from OpenAlex

In February 2021, the University of Alberta (U of A) partnered with the Cure Cancer Foundation and the World's Longest Game to hold the World's Longest Hockey Game to raise funds for the clinical trials for PCLX-001, a new drug to treat breast and blood cancers. The fundraising component of this 11-day event primarily utilised a peer-to-peer approach and was hosted on the U of A's crowdfunding platform. This paper aims to provide insight and recommend best practices for turning an event into a large-scale fundraising effort. The analysis will cover technical and logistical setup, as well as the outreach strategies that were a key part of the crowdfunding model's success. Also explored will be the storytelling, management and messaging necessary to create an authentic sense of community and meaningfully engage shareholders.

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 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)0.020
metaresearch head score (Gemma)0.107
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.107
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.337
GPT teacher head0.531
Teacher spread0.194 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2023
Admission routes2
Has abstractyes

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