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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 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)0.014
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0030.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.1480.096

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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
GenreMethods

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
Published2025
Admission routes1
Has abstractyes

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