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Record W2605486355 · doi:10.1093/jmp/jhx006

Truth or Spin? Disease Definition in Cancer Screening

2017· article· en· W2605486355 on OpenAlex
Lynette Reid

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Medicine and Philosophy A Forum for Bioethics and Philosophy of Medicine · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsDalhousie University
Fundersnot available
KeywordsReductionismEpistemologyDiseaseObjectivity (philosophy)AppealPhilosophy of medicineContext (archaeology)PsychologyPhilosophy of scienceScope (computer science)MedicinePhilosophyPathologyAlternative medicinePolitical scienceBiologyComputer scienceLaw

Abstract

fetched live from OpenAlex

Are the small and indolent cancers found in abundance in cancer screening normal variations, risk factors, or disease? Naturalists in philosophy of medicine turn to pathophysiological findings to decide such questions objectively. To understand the role of pathophysiological findings in disease definition, we must understand how they mislead in diagnostic reasoning. Participants on all sides of the definition of disease debate attempt to secure objectivity via reductionism. These reductivist routes to objectivity are inconsistent with the Bayesian nature of clinical reasoning; when they appeal to the sciences, they are inconsistent with what philosophy of biology tells us about its natural kinds. Proposals that we narrow the scope of our claims in the disease definition debates (proposing adoption of a specific disease paradigm for a specific context) are useful, but paradigms can still distort our reasoning in particular cases, even when we are self-conscious about their status.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.312
GPT teacher head0.410
Teacher spread0.098 · 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