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Reader Comments

2016· article· en· W4231733173 on OpenAlexaff
Sophie Gosselin, Lotte C. G. Hoegberg, Bryan D. Hayes, Marc Ghannoum, Robert S. Hoffman, Chibuzo Odigwe, Madiha Tariq, Kizito Ojiako, Nkem Iroegbu

Bibliographic record

VenueBaylor University Medical Center Proceedings · 2016
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsUniversité de MontréalMcGill University Health Centre
Fundersnot available
KeywordsComputer sciencePsychology

Abstract

fetched live from OpenAlex

"Reader Comments." Baylor University Medical Center Proceedings, 29(4), pp. 444–445

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)0.007
metaresearch head score (Gemma)0.094
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.796
Threshold uncertainty score0.681

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.094
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0050.003
Scholarly communication0.0090.004
Open science0.0030.004
Research integrity0.0290.021
Insufficient payload (model declined to judge)0.2040.143

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 head0.015
GPT teacher head0.238
Teacher spread0.222 · 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.

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".

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Citations0
Published2016
Admission routes1
Has abstractno

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