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Record W2121294346 · doi:10.3747/co.21.2263

Systemic Treatment Safety Symposium 2014: Oral Chemotherapy

2014· article· en· W2121294346 on OpenAlexafffundvenueabout
Vicky Simanovski, Laura Grau, M. Wright, Erin Rae, Noor Ani Ahmad, K. Creber, E. Green, Kathy Vu, Vishal Kukreti, Monika K. Krzyzanowska

Bibliographic record

VenueCurrent Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreCredit Valley Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineScope (computer science)Work (physics)Medical prescriptionMedical educationNursingEngineering

Abstract

fetched live from OpenAlex

The second Systemic Treatment Safety Symposium, which took place February 21, 2014, in Toronto, aimed to identify opportunities for improving the delivery of systemic cancer treatment in Ontario based on regional needs, while providing a venue for collaboration and knowledgesharing. The agenda included a series of panel sessions followed by discussions, presentations of regional improvement projects and results, and breakout sessions. Based on the discussion that took place at the symposium, a provincial goal of zero handwritten or verbal oral chemotherapy orders by June 30, 2015, has now been established, and regions will be provided with funding for safe prescribing initiatives to support achievement of that aim. Building on the lessons learned from the 2014 System Treatment Safety Symposium, a common measurement strategy will be identified, and Cancer Care Ontario (cco) will also support the work by identifying the recommended key elements of a safe oral chemotherapy prescription. Additionally, cco will identify areas for improving systemic treatment computerized prescriber order entry systems to better enable prescribing of oral agents within such systems. Among the most prominent of the lessons learned during the symposium was the importance of having a focused topic (such as oral chemotherapy) while maintaining a province-wide scope. Another significant takeaway was that attendees appreciate the opportunity to hear from colleagues across the province about the work underway in various regions. Future safety symposia will also explore opportunities for enhanced engagement with participants through greater use of technology.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.144
GPT teacher head0.472
Teacher spread0.328 · 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 designNot applicable
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

Citations1
Published2014
Admission routes4
Has abstractyes

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