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Record W2068598833 · doi:10.1097/acm.0b013e31829a3c32

Is Clinical Cognition Binary or Continuous?

2013· letter· en· W2068598833 on OpenAlexaff
Geoffrey R. Norman, Sandra Monteiro, Jonathan Sherbino

Bibliographic record

VenueAcademic Medicine · 2013
Typeletter
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDual (grammatical number)Dual process theory (moral psychology)Unconscious mindProcess (computing)CognitionVariety (cybernetics)Computer scienceTask (project management)Cognitive psychologyCognitive sciencePsychologyArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

A dominant theory of clinical reasoning is the so-called "dual processing theory," in which the diagnostic process may proceed through a rapid, unconscious, intuitive process (System 1) or a slow, conceptual, analytical process (System 2). Diagnostic errors are thought to arise primarily from cognitive biases originating in System 1. In this issue, Custers points out that this model is unnecessarily restrictive and that it is more likely that diagnostic tasks may proceed through a variety of mental strategies ranging from "analytical" to "intuitive."The authors of this commentary agree that the notion that System 1 and System 2 processes are somehow in competition and will necessarily lead to different conclusions is unnecessarily restrictive. On the other hand, they argue that there is substantial evidence in support of a dual processing model, and that most objections to dual processing theory can be easily accommodated by simply presuming that both processes operate in concertand that solving any task may rely to varying degrees on both processes.

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)0.006
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.080
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.015
Scholarly communication0.0040.008
Open science0.0020.002
Research integrity0.0180.015
Insufficient payload (model declined to judge)0.0040.001

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 head0.129
GPT teacher head0.440
Teacher spread0.311 · 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 designTheoretical or conceptual
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

Citations24
Published2013
Admission routes1
Has abstractyes

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