{"id":"W4237118080","doi":"10.4018/978-1-5225-5484-4.ch027","title":"Enhancing Self-Reflection With Wearable Sensors Workshop","year":2018,"lang":"en","type":"book-chapter","venue":"Wearable Technologies","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reflection (computer programming); Wearable computer; Computer science; Data science; Wearable technology; Human–computer interaction; Engineering; Engineering ethics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004804016,0.0006926329,0.0007928021,0.0008281866,0.0003966786,0.0005080644,0.001490299,0.001147537,0.0001594223],"category_scores_gemma":[0.0001139565,0.0006193182,0.0001681898,0.0004428508,0.0002929707,0.000904928,0.0006878451,0.001115431,0.002103812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003941024,"about_ca_system_score_gemma":0.000246815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004007821,"about_ca_topic_score_gemma":0.0003046265,"domain_scores_codex":[0.9967015,0.00004418196,0.0005306386,0.00133871,0.0006841064,0.0007008822],"domain_scores_gemma":[0.9966999,0.0002750877,0.0005931429,0.001919562,0.0004408418,0.00007143222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002734986,0.0004766747,0.0001495111,0.001443313,0.003359509,0.001003825,0.004495579,0.0001565318,0.009769412,0.0637688,0.03724339,0.87786],"study_design_scores_gemma":[0.001579333,0.00173353,0.00001684256,0.01223417,0.0002859405,0.001582961,0.002046287,0.002679504,0.1215218,0.09840653,0.7530959,0.0048172],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002882581,0.007609109,0.1982824,0.002541667,0.002029464,0.002297185,0.00001603884,0.03807813,0.7462634],"genre_scores_gemma":[0.1332594,0.002813933,0.05048246,0.0001419442,0.0003887474,0.0002574481,0.000005870702,0.0002633521,0.8123868],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8730428,"threshold_uncertainty_score":0.9996258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02674390644269323,"score_gpt":0.2428038416609923,"score_spread":0.216059935218299,"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."}}