MétaCan
Menu
Back to cohort
Record W2320105571 · doi:10.1097/acm.0b013e31828c4ae0

Redesigning the MCAT Exam

2013· article· en· W2320105571 on OpenAlexaboutno aff
Richard M. Schwartzstein, Gary C. Rosenfeld, Robert C. Hilborn, Saundra Herndon Oyewole, Karen Mitchell

Bibliographic record

VenueAcademic Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsnot available
Fundersnot available
KeywordsBlueprintMedical educationTest (biology)Experiential learningPsychologyProcess (computing)MedicinePedagogyComputer scienceEngineering

Abstract

fetched live from OpenAlex

The authors of this commentary discuss the recently completed review of the current Medical College Admission Test (MCAT), which has been used since 1991, and describe the blueprint for the new test that will be introduced in 2015. The design of the MCAT exam reflects changes in medical education, medical science, health care delivery, and the needs of the populations served by graduates of U.S. and Canadian medical schools. The authors describe how balancing the ambitious goals for the new exam and the varying priorities of the testing program's many stakeholders made blueprint design complex. They discuss the tensions and trade-offs that characterized the design process as well as the deliberations and data that shaped the blueprint.The blueprint for the MCAT exam balances the assessment of a broad range of competencies in the natural, social, and behavioral sciences and critical analysis and reasoning skills that are essential to entering students' success in medical school. The exam will include four sections: Biological and Biochemical Foundations of Living Systems; Chemical and Physical Foundations of Biological Systems; Psychological, Social, and Biological Foundations of Behavior; and Critical Analysis and Reasoning Skills.The authors also offer recommendations for admission committees, advising them to review applicants' test scores, course work, and other academic, personal, and experiential credentials as part of a holistic admission process and in relation to their institutions' educational, scientific, clinical, and service-oriented goals.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0350.001

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 head0.074
GPT teacher head0.379
Teacher spread0.304 · 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
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

Citations61
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAcademic MedicineSame topicMedical Education and AdmissionsFrench-language works237,207