{"id":"W7165057639","doi":"10.2196/81439","title":"A Smart Phone App to Improve Intuitive Eating and Diet Quality: Design and Usability Study (Preprint)","year":2025,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Usability; Smart phone; Phone; Affect (linguistics); Mobile device","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002408362,0.0007038635,0.0006076797,0.0007192234,0.0004486771,0.0006309547,0.0004630651,0.0007202383,0.005089882],"category_scores_gemma":[0.004061582,0.0004355544,0.0006134678,0.0002664753,0.0003178613,0.0006105161,0.0006262431,0.0003327013,0.0006358387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001600793,"about_ca_system_score_gemma":0.0005018588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006830439,"about_ca_topic_score_gemma":0.001111471,"domain_scores_codex":[0.9992418,0.0003192417,0.00009017398,0.0001417462,0.0001362474,0.00007078565],"domain_scores_gemma":[0.9969547,0.002239257,0.0000831504,0.0001339008,0.0004443517,0.0001446132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.02444609,0.04140687,0.04841253,0.009263688,0.0007222081,0.001433342,0.01833467,0.001294226,0.156806,0.0007281231,0.006763563,0.6903887],"study_design_scores_gemma":[0.01567998,0.4221691,0.3863235,0.001313453,0.004915091,0.002641118,0.01313341,0.01571977,0.1031978,0.0008349224,0.03351822,0.0005536507],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875919,0.0002525374,0.008197674,0.0001067151,0.00009216795,0.002162577,0.0003241859,0.0002466631,0.0010256],"genre_scores_gemma":[0.9050663,0.0006451751,0.07917912,0.0005571252,0.00008132683,0.00724954,0.0004498451,0.0001595477,0.006611995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005089882,"threshold_uncertainty_score":0.01702732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08390866023021838,"score_gpt":0.4740051706133956,"score_spread":0.3900965103831773,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}