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Record W2308440414 · doi:10.1177/0956797616634068

On the Necessity of Distinguishing Between Unintentional and Intentional Mind Wandering

2016· article· en· W2308440414 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

VenuePsychological Science · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMind-wanderingPsychologyConstruct (python library)PhenomenonCognitive psychologyTheory of mindEpistemologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

In recent years, there has been an enormous increase in the number of studies examining mind wandering. Although participants' reports of mind wandering are often assumed to largely reflect spontaneous, unintentional thoughts, many researchers' conceptualizations of mind wandering have left open the possibility that at least some of these reports reflect deliberate, intentional thought. Critically, however, in most investigations on the topic, researchers have not separately assessed each type of mind wandering; instead, they have measured mind wandering as a unitary construct, thereby conflating intentional and unintentional types. We report the first compelling evidence that an experimental manipulation can have qualitatively different effects on intentional and unintentional types of mind wandering. This result provides clear evidence that researchers interested in understanding mind wandering need to consider the distinction between unintentional and intentional occurrences of this phenomenon.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.121
GPT teacher head0.362
Teacher spread0.241 · 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