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Record W4393072249 · doi:10.4324/b23293-18

Canadian Life Care Planning and Cost Projection Analysis

2024· book-chapter· en· W4393072249 on OpenAlexaboutno aff
Claudia von Zweck, Dana Weldon

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsProjection (relational algebra)Computer scienceAlgorithm

Abstract

fetched live from OpenAlex

A life care plan is a dynamic document that outlines the lifelong needs of an individual following a catastrophic injury or chronic illness. Life care plans are designed to reduce disability, promote participation in productive activity, and ensure best use of available funding and other resources needed for optimal quality of life following an injury or illness. Basic tenets underlying the life care planning process in Canada include objectivity, evidence-informed practice, credibility, comprehensiveness, balance, ethical behaviour, and person-centredness. While development of a life care plan usually follows a sequential order, work may occur concurrently on several steps in a process that involves referral, consent, file review, assessment, review of research literature, formulation of recommendations, and evaluation. Life care planners may be asked to critique the report of another planner to understand weaknesses in the reviewed life care plan. Areas of examination for the critique include the file review, plan structure and accuracy, evaluation methods, theory or foundation, and costing. Additionally, life care planners may be called upon to serve as expert witnesses in a Canadian court. When providing testimony, the objective is to assist the court in deciding the facts by providing information that is pertinent and relevant to the case without being an advocate for one side or the other. In this way life care plans are useful for the affected individuals and their caregivers, as well as for the courts to ensure required services and products are available as needed over time and throughout the life span.

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)0.003
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.862
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.013
Science and technology studies0.0030.001
Scholarly communication0.0040.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.002

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 head0.089
GPT teacher head0.380
Teacher spread0.291 · 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
Published2024
Admission routes1
Has abstractyes

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