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Record W2321599906 · doi:10.1016/j.janxdis.2016.03.011

Fear of the unknown: One fear to rule them all?

2016· review· en· W2321599906 on OpenAlexafffund
R. Nicholas Carleton

Bibliographic record

VenueJournal of Anxiety Disorders · 2016
Typereview
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of Regina
FundersCanadian Institutes of Health Research
KeywordsPsychologyPropositionAnxietyNeuroticismRhetorical questionReductionismPsychotherapistCognitive psychologyEpistemologySocial psychologyPersonalityPsychiatryLinguistics

Abstract

fetched live from OpenAlex

The current review and synthesis was designed to provocatively develop and evaluate the proposition that "fear of the unknown may be a, or possibly the, fundamental fear" (Carleton, 2016) underlying anxiety and therein neuroticism. Identifying fundamental transdiagnostic elements is a priority for clinical theory and practice. Historical criteria for identifying fundamental components of anxiety are described and revised criteria are offered. The revised criteria are based on logical rhetorical arguments using a constituent reductionist postpositivist approach supported by the available empirical data. The revised criteria are then used to assess several fears posited as fundamental, including fear of the unknown. The review and synthesis concludes with brief recommendations for future theoretical discourse as well as clinical and non-clinical research.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0050.006
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.066
GPT teacher head0.375
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations633
Published2016
Admission routes2
Has abstractyes

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