{"id":"W4376643274","doi":"10.2196/46659","title":"Automated Diet Capture Using Voice Alerts and Speech Recognition on Smartphones: Pilot Usability and Acceptability Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Usability; Logging; Computer science; Medicine; Human–computer interaction; Forestry","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":[0.004649605,0.0009647962,0.0009180357,0.0005117123,0.000367153,0.0006970848,0.0005904915,0.0006327665,0.002163902],"category_scores_gemma":[0.008216091,0.0003741279,0.0008027882,0.0001767595,0.0003948215,0.0007190867,0.0008459577,0.0004054528,0.0004091302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002134772,"about_ca_system_score_gemma":0.0003643047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007079107,"about_ca_topic_score_gemma":0.001215992,"domain_scores_codex":[0.9973263,0.001484572,0.0002174885,0.0003141485,0.0004533566,0.0002042021],"domain_scores_gemma":[0.9923877,0.004493437,0.0003676699,0.0004409599,0.001925835,0.0003844668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.03466018,0.06639576,0.2033438,0.005749993,0.001320323,0.003471497,0.02906835,0.002588043,0.264463,0.0003236551,0.003945422,0.38467],"study_design_scores_gemma":[0.004373674,0.4494616,0.4575641,0.0003829923,0.001928127,0.003090597,0.01164106,0.01507182,0.04914873,0.0002424352,0.006809931,0.0002848198],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968754,0.00006093805,0.001995333,0.00003204171,0.00001334389,0.0006313853,0.00008414793,0.0000471178,0.0002602041],"genre_scores_gemma":[0.9848807,0.0002050194,0.01197472,0.0001210192,0.00004368064,0.001670092,0.0001954644,0.00002716086,0.0008821519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004649605,"threshold_uncertainty_score":0.02458978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1601631390695426,"score_gpt":0.4473296009493426,"score_spread":0.2871664618798,"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."}}