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Record W2100881081 · doi:10.1177/0163278713518942

Notes From the Field

2014· article· en· W2100881081 on OpenAlexaff
Irene Ma, Nadia Zalunardo, Mary Brindle, Rose Hatala, Kevin McLaughlin

Bibliographic record

VenueEvaluation & the Health Professions · 2014
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsModalitiesChecklistModality (human–computer interaction)Video recordingReliability (semiconductor)Video qualityMedicineMedical physicsComputer sciencePsychologyMultimediaArtificial intelligenceCognitive psychologyOperations managementEngineering

Abstract

fetched live from OpenAlex

Blinded assessments of technical skills using video-recordings may offer more objective assessments than direct observations. This study seeks to compare these two modalities. Two trained assessors independently assessed 18 central venous catheterization performances by direct observation and video-recorded assessments using two tools. Although sound quality was deemed adequate in all videos, portions of the video for wire handling and drape handling were frequently out of view (n = 13, 72% for wire-handling; n = 17, 94% for drape-handling). There were no differences in summary global rating scores, checklist scores, or pass/fail decisions for either modality (p > 0.05). Inter-rater reliability was acceptable for both modalities. Of the 26 discrepancies identified between direct observation and video-recorded assessments, three discrepancies (12%) were due to inattention during video review, while one (4%) discrepancy was due to inattention during direct observation. In conclusion, although scores did not differ between the two assessment modalities, techniques of video-recording may significantly impact individual items of assessments.

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)0.002
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.213
Threshold uncertainty score0.711

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2130.060

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 head0.151
GPT teacher head0.487
Teacher spread0.336 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEvaluation & the Health ProfessionsSame topicCentral Venous Catheters and HemodialysisFrench-language works237,207