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Record W3005009135 · doi:10.1055/s-0040-1702409

Quality from the Patient’s Perspective: Implementation of an Established Patient-Reported Outcome Platform in a Multidisciplinary Skull Base Tumor Clinic

2020· article· en· W3005009135 on OpenAlexaff
Stephanie Flukes, Jennifer R. Cracchiolo, Eliza B. Geer, David Goldstein, John R. de Almeida, Vivian Tabar, Marc A. Cohen

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2020
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMultidisciplinary approachMedicinePerspective (graphical)Multidisciplinary teamSkullQuality managementPatient careIntensive care medicineQuality of life (healthcare)Medical physicsMedical emergencySurgeryNursingOperations managementComputer scienceManagement systemArtificial intelligence

Abstract

fetched live from OpenAlex

Background: Utilization of patient-reported outcomes (PROs) in clinical care for skull base tumor patients treated in a multidisciplinary management team has been proposed to focus on outcomes most important to patients and to enhance shared decision making. Specific options for treatment, including endoscopic and open surgery as well as chemoradiation have both acute and long-term sequelae. Identification of how these treatments impact the individual patient has implications for both quality of care and the value of the treatment provided.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.399
Teacher spread0.247 · 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.

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
Published2020
Admission routes1
Has abstractyes

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