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Record W2937518181 · doi:10.1007/s12630-019-01361-4

The MacGyver bias and attraction of homemade devices in healthcare

2019· editorial· fr· W2937518181 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2019
Typeeditorial
Languagefr
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsAttractionHealth careBusinessComputer sciencePolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Angus ''Mac'' MacGyver is arguably one of the most famous fictional characters in modern pop culture. In the original television series (that aired from 1985 to 1992), MacGyver routinely overcame seemingly insoluble problems under time pressure with nothing more than readily available items (e.g., a Swiss Army knife, paper clip, and a chewing gum wrapper), common sense, and scientific acumen. This think-on-your-feet approach has held such a decades-long widespread appeal that ''MacGyver'' has become part of the modern vernacular, including its entry as a verb into the Oxford English Dictionary: ''To make or repair (an object) in an improvised or inventive manner, making use of whatever items are at hand.'' 1

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.003
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 head0.023
GPT teacher head0.240
Teacher spread0.217 · 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