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Record W2085309081 · doi:10.1080/15265161.2015.1009565

Infection Control Measures and Debts of Gratitude

2015· letter· en· W2085309081 on OpenAlexaffabout
Diego S. Silva, A. M. Viens

Bibliographic record

VenueThe American Journal of Bioethics · 2015
Typeletter
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsGratitudeDebtPsychologyLibrary scienceSociologySocial psychologyEconomicsFinanceComputer science

Abstract

fetched live from OpenAlex

Diego S. Silvaa* & A. M. Viensba Medizinische Hochschule Hannover, St. Michael's Hospital, Toronto, and University of Toronto b University of Southampton Address correspondence to Diego S. Silva, Institut für Geschichte, Ethik und Philosophie der Medizin, OE 5450, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, D-30625 Hannover, Germany. E-mail: silva.diego@mh-hannover.de

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)0.009
metaresearch head score (Gemma)0.057
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.033
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0330.033
Insufficient payload (model declined to judge)0.0070.002

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 head0.147
GPT teacher head0.477
Teacher spread0.329 · 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
GenreCommentary

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

Citations6
Published2015
Admission routes2
Has abstractyes

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