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Record W7044013871

A Utilização De Terminologias Em Saúde

2020· other· en· W7044013871 on OpenAlexaboutno aff

Bibliographic record

VenueUNIFESP Institutional Repository (Universidade Federal de São Paulo) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationCommissionHealth careData collectionDescriptive researchPsychological interventionPublic healthSample (material)Public healthcarePlan (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Objective: Identify The Use Of Terminologies In The Healthcare Service Providers And Health Plan Operators, With The Aim Of Verifying The Terminologies Used For Procedures And Interventions And Also To Know Their Purpose Of Use, Governance Processes And Storage. Methods: This Is A Descriptive Research That Aims To Present The Characteristics Of Application Of The Subject Matter, Involving The Use Of Standardized Techniques Of Data Collection Through A Questionnaire, Validated By Specialists And Containing 39 (Thirty-Nine) Open And Closed Questions. The Sample Selection Criterion For The Questionnaire Were: Public And Private Hospitals, Accredited By Joint Commission International (Jci) And Accreditation Canada International (Aci), Health Plan Operators, Laboratories And Telehealth"S Organizations With Healthcare Delivery. Also, For Convenience, It Was Decided That The Institutions Would Be Located In The State Of São Paulo. Results: The Questionnaire Was Applied In 32 (Thirty-Two) Institutions. Of These, 16 (

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)0.036
metaresearch head score (Gemma)0.083
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.083
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.009
Science and technology studies0.0030.007
Scholarly communication0.0050.007
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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 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
Published2020
Admission routes1
Has abstractyes

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Same venueUNIFESP Institutional Repository (Universidade Federal de São Paulo)French-language works237,207