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Record W2338457097 · doi:10.1097/acm.0000000000001107

Additional Considerations for the Expert–Generalist Model

2016· letter· en· W2338457097 on OpenAlexaboutno aff
Edward J. Volpintesta

Bibliographic record

VenueAcademic Medicine · 2016
Typeletter
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSpecialtyBurnoutPrimary careMalpracticeAdversarial systemPrimary care physicianSet (abstract data type)Work (physics)Medical carePsychologyMedicineFamily medicinePolitical scienceLawComputer scienceEngineering

Abstract

fetched live from OpenAlex

To the Editor: Although the idea of expanding primary care physicians’ (PCPs’) skills to include some specialty skills1 sounds good and may work well in some areas of rural Canada, it would be difficult and even dangerous for PCPs here in the United States. In fact, the results could be disastrous. First, in primary care in the United States the burden of administrative demands is extraordinarily onerous, and it alone has already brought on burnout in many PCPs. These doctors’ energies and emotional reserves are already stretched to the maximum, and any further strain would be ill conceived and lead to disaster. Second, the U.S. litigation system is extremely aggressive and adversarial. Using PCPs to provide services beyond their usual skill set greatly increases their vulnerability to malpractice suits. If specialists are seeing problems that they feel should be seen by a PCP then they should charge fees similar to what a PCP would charge. That is a better way of controlling costs. Edward Joseph Volpintesta, MD President, Bethel Medical Group, Bethel, Connecticut; [email protected]

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)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.301
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.3020.001

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 head0.273
GPT teacher head0.496
Teacher spread0.223 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2016
Admission routes1
Has abstractyes

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