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Record W2120532132

Bridging the gap between primary care and the cancer system: the UPCON Network of CancerCare Manitoba.

2009· article· en· W2120532132 on OpenAlexaffabout
Jeffrey Sisler, Pat McCormack-Speak

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsOutreachPrimary careCancerMedicineContinuing medical educationAgency (philosophy)Family medicineBridging (networking)NursingCancer geneticsContinuing educationMedical educationComputer sciencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM BEING ADDRESSED: Patient care is poorly coordinated between family physicians and the cancer system and the working relationships are not strong. OBJECTIVE OF PROGRAM: To improve integration of patient care and communication between FPs and cancer specialists; enhance FPs' knowledge of cancer and the cancer system; and promote the role of primary care within the cancer care system. PROGRAM DESCRIPTION: The Uniting Primary Care and Oncology (UPCON) Network of CancerCare Manitoba has created partnerships with 12 primary care clinics in Winnipeg, Man, by providing the following: access to the provincial electronic medical record for cancer; small group continuing professional development for a "lead physician" from each clinic to make him or her the local cancer resource; educational outreach to all clinic staff; and changes within CancerCare Manitoba to highlight the role of FPs. CONCLUSION: Lead physicians are appreciated by their clinic colleagues, and these FPs are the main users of the cancer electronic medical record. A strong cancer continuing professional development program has been implemented and a voice for primary care has been created within the agency. The UPCON Network is now expanding throughout Manitoba.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.060
GPT teacher head0.274
Teacher spread0.214 · 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 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

Citations25
Published2009
Admission routes2
Has abstractyes

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