{"id":"W4225007751","doi":"10.2196/34606","title":"Designing Tangibles to Support Emotion Logging for Older Adults: Development and Usability Study","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council","keywords":"Usability; Psychology; Human–computer interaction; Logging; Pluralistic walkthrough; Computer science; Applied psychology; Geography","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":[0.005317103,0.0008318654,0.0004529622,0.0009389199,0.0004253703,0.001266269,0.0006167558,0.0007870016,0.002271803],"category_scores_gemma":[0.01394157,0.0004026429,0.0008136771,0.000420625,0.0005218621,0.001333238,0.001122524,0.000463761,0.0003258695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002880341,"about_ca_system_score_gemma":0.0005584062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005415154,"about_ca_topic_score_gemma":0.00124086,"domain_scores_codex":[0.9984584,0.0007779075,0.0002306127,0.0001543239,0.0002639221,0.0001148095],"domain_scores_gemma":[0.9902273,0.007463967,0.0003644011,0.0005687271,0.001077648,0.0002979038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001758842,0.006012736,0.07480864,0.01221438,0.0004072572,0.00444885,0.06104469,0.002858388,0.1101195,0.001843212,0.00660859,0.7178749],"study_design_scores_gemma":[0.003052932,0.06370647,0.5184422,0.009763536,0.002748509,0.01432282,0.0686188,0.02698218,0.1101799,0.003284633,0.1777462,0.00115178],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9581428,0.001210227,0.03401616,0.000242373,0.00009412391,0.002589506,0.0003268135,0.0004372141,0.002940821],"genre_scores_gemma":[0.831628,0.001440503,0.1609812,0.0002644658,0.00004236188,0.002505236,0.000370653,0.0001117024,0.002655872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005317103,"threshold_uncertainty_score":0.02811986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04223038633709397,"score_gpt":0.3241057179647601,"score_spread":0.2818753316276661,"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."}}