MétaCan
Menu
Back to cohort
Record W3199275610

PSYCHOLOGY OF DIETING

2019· article· en· W3199275610 on OpenAlexvenueno aff
Saroosh Fatima

Bibliographic record

VenueAdvanced Food and Nutritional Sciences · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDietingSurprisePsychologySocial psychologyTask (project management)Everyday lifeWorryWeight lossAnxietyMedicineObesityPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Dieting is not an easy task especially for people who love to eat and try out different types of meal everyday. It is very general human behavior that we don't like the idea of restrictions. Now even if maintaining a healthy diet is not particularly liked by everyone. For some people it is something they must adopt in their daily life. Psychology plays a vital role in making it beneficial and easier. If a person thinks that restraining from eating a whole lot of meals everyday and being super conscious and aware of what is going in our stomach is a very different task. It will be no surprise that he or she will find it difficult to achieve a healthy diet. Similarly, if you are extra sensitive and over conscious about your diet it means you are panicking about your weight gain as a result you might end up eating more than usual. Many people have a habit of stress eating. Other times people stop eating at all because their weight psychologically disturbs them to a great extent. Since psychology is so important in weight change journey it should be observed that a person is psychologically focused and attentive while eating their meals. Munching on random snacks while watching a movie or whole talking to someone is a big no. A balance between over conscious and not being conscious at all should be maintained. In a nutshell, psychologically strong people or the people who don't worry a lot about weight changes tend to lose or gain more weight depending on their desires.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.353

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 head0.074
GPT teacher head0.482
Teacher spread0.407 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced Food and Nutritional SciencesSame topicHealth and Lifestyle StudiesFrench-language works237,207