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Record W6946211077 · doi:10.3389/fmed.2022.997277.s001

Data_Sheet_1_Decision making under uncertainty in the diagnosis and management of Alzheimer's Disease in primary care: A study protocol applying concepts from neuroeconomics.pdf

2022· dataset· en· W6946211077 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldComputer Science
TopicNetwork Packet Processing and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Primary careDiseaseDisease managementMEDLINERisk management

Abstract

fetched live from OpenAlex

Background<p>The current management of patients with Dementia, primarily with Alzheimer's Disease (AD) is rapidly evolving. However, limited information is available about the current gaps and decision-making in primary care.</p>Objectives<p>To evaluate factors associated with gaps, risk preferences regarding diagnostic and therapeutic choices in the management of patients with AD by primary care physicians (PCP) from across Canada.</p>Methods<p>We propose a non-interventional, cross-sectional pilot study involving 120 primary care physicians referred from the College of Family Physicians of Canada to assess diagnostic and therapeutic decisions in the management of ten simulated AD-related case-scenarios commonly encountered in clinical practice. We initially describe the current landscape and gaps regarding diagnostic and therapeutic challenges in the management of patients with AD in primary care. Then, we provide concepts from behavioral economics and neuroeconomics applied to medical decision-making. Specifically, we include standardized tests to measure risk aversion, physicians' reactions to uncertainty, and questions related to risk preferences in different domains. Finally, we summarize the protocol to be implemented to address our goals. The primary study outcome is the proportion of participants that elect to defer initial investigations to the specialist and the associated factors. Secondary outcomes include the proportion of PCP willing to order cerebral spinal fluid studies, PET scans, or initiate treatment according to the simulated case-scenarios. The study will be conducted in English and French.</p>Conclusions<p>The study findings will contribute a better understanding of relevant factors associated with diagnostic and therapeutic decisions of PCP in the management of AD, identifying participant's preferences and evaluating the role of behavioral aspects such tolerance to uncertainty, aversion to ambiguity, and therapeutic inertia.</p>

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.154
Threshold uncertainty score0.994

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 science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.063
GPT teacher head0.338
Teacher spread0.275 · 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