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Record W2749945512 · doi:10.5357/koubyou.84.1_37

Systemic Condition of First-visit Patients to the Periodontics Section of Tokyo Medical and Dental University Hospital

2017· article· en· W2749945512 on OpenAlexaff
Norio Aoyama, Tomonari Suda, Yuichi Ikeda, Ena KINEBUCHI, Takayuki Sekiuchi, Tatsuro Koyanagi, Sae Hayakumo, Koji Mizutani, Tatsuya Akizuki, Yuichi Izumi

Bibliographic record

VenueTHE JOURNAL OF THE STOMATOLOGICAL SOCIETY JAPAN · 2017
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPeriodontologySection (typography)MedicineDentistryUniversity hospitalFamily medicineBusiness

Abstract

fetched live from OpenAlex

研究目的 : 歯周病と全身疾患の関連が示されてきているが, その関係性については知られていない点が多い。本研究の目的は, 大学病院歯周病外来に初診で来院した患者の全身疾患の状態を調査し, 歯周病の状態と比較することである。

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

Explore more

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