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Record W4253638248 · doi:10.1159/000447463

Scientific Programme

2016· article· en· W4253638248 on OpenAlexaff

Bibliographic record

VenueEuropean Thyroid Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
FundersMedical Center, University of RochesterUniversità degli Studi di FerraraUniversitat Autònoma de BarcelonaUniversität zu LübeckUniversità Cattolica del Sacro CuoreUniversità degli Studi di PerugiaUniversità di PisaMuséum National d'Histoire NaturelleNational University of SingaporeUniversitat de BarcelonaUniversité Paris DiderotUniversità degli Studi di TorinoUniversità degli Studi di FirenzeUniversità degli Studi di VeronaUniversity of GlasgowKarolinska InstitutetMagyar Tudományos AkadémiaKosin UniversityUniversity of RochesterCollege of Medicine, Koisin UniversityUniversiteit van AmsterdamSwansea UniversityCardiff UniversityUniversità degli Studi di Milano
KeywordsMedicineFamily medicine

Abstract

fetched live from OpenAlex

Who should be screened for thyroid nodules

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)0.011
metaresearch head score (Gemma)0.035
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 score0.822
Threshold uncertainty score0.595

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.1780.079

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 head0.027
GPT teacher head0.258
Teacher spread0.231 · 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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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