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Record W1989272119 · doi:10.1057/biosoc.2013.6

Biomarkers, the molecular gaze and the transformation of cancer survivorship

2013· article· en· W1989272119 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.

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

Bibliographic record

VenueBioSocieties · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDiseaseGazeValue (mathematics)CancerVulnerability (computing)Meaning (existential)PsychologyMedicinePathologyPsychotherapistInternal medicine

Abstract

fetched live from OpenAlex

Over the past two decades, molecular technologies have transformed the landscape of cancer diagnosis, treatment and disease surveillance. However, although the effects of these technologies in the areas of primary and secondary cancer prevention have been the focus of growing study, their role in tertiary prevention remains largely unexamined. Treating this topic as a problematic to be conceptually explored rather than empirically demonstrated, this article focuses on the molecularisation of tertiary prevention, especially the growing use of molecular biomarkers to monitor disease recurrence. Taking a semiotic approach, I speculate on the potential meanings of molecular biomarkers for people living with and beyond cancer and suggest the meanings of these technologies may differ in important ways for those on both sides of the risk divide: that is, those 'at risk' for cancer and those living with realised risk. Although molecular biomarkers may intensify a sense of 'measured vulnerability', by indexing cancer's presence they may also prove reassuring. Moreover, as an invisible but ostensibly 'transparent' sign, in some contexts they appear to enable cancer survivors to challenge biomedical decision making. In the light of recent oncological debates about the value of these biomarkers in tertiary prevention, I conclude by suggesting that signs can never be reduced to their 'objective' biomedical denotation in spite of professional attempts to expunge meaning and value from care.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.221

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 science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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