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Record W7134217033 · doi:10.4992/pacjpa.89.0_122

Explanation of COSMIN Guidelines version 2.0

2025· article· en· W7134217033 on OpenAlexaff
Hideki Sato, 土屋 雅勇

Bibliographic record

VenueThe Proceedings of the Annual Convention of the Japanese Psychological Association · 2025
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsAdvantage Forensics (Canada)
Fundersnot available
KeywordsFeature (linguistics)Task (project management)Set (abstract data type)Context (archaeology)Identification (biology)

Abstract

fetched live from OpenAlex

心理学では毎年数千の新しい構成概念や尺度が発表され,その大半は非常に少ない回数しか使用されていないことが問題視されている(Anvari et al., 2024)。患者報告式アウトカム(PRO)とは,臨床家その他の誰の解釈も介さず,患者から直接得られた,患者の健康状態に関するあらゆる報告と定義され(FDA, 2009),主に医療分野で用いられる心理尺度は患者報告式アウトカム尺度(PROM)と呼ばれる。測定したい構成概念や研究および臨床実践に最適なPROMを選んで利用するためには,研究の方法論上の質(バイアスのリスク)や,PROMの信頼性や妥当性といったさまざまな測定特性を批判的に吟味する必要がある。こうした中,COSMINとは健康関連尺度の選択に関する合意に基づく指針であり,PROM研究の評価および報告に関するガイドラインなどが整備されている。そこで本チュートリアル・ワークショップでは,2024年に2度目の改定がなされたPROMの系統的レビューに関するCOSMINガイドライン第2版とCOSMINバイアスのリスクチェックリスト第3版(Mokkink et al., 2024)を解説する。

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.320
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.331
Teacher spread0.310 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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