{"id":"W2541234445","doi":"","title":"Expanding the Information Fidelity of Calm Technology Devices Through Techniques of Information Visualization","year":2016,"lang":"en","type":"dissertation","venue":"OCAD University Open Research Repository (OCAD University)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario College of Art and Design","funders":"","keywords":"Visualization; Fidelity; Information visualization; Computer science; Human–computer interaction; Reflection (computer programming); Information technology; Engineering; Data science; Artificial intelligence; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005786141,0.0009261219,0.0007506108,0.002228368,0.001295949,0.009218454,0.001978695,0.001414468,0.005518124],"category_scores_gemma":[0.03219288,0.0007333122,0.0008633866,0.001529566,0.003504539,0.01222869,0.008067099,0.002259774,0.0007064951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001009379,"about_ca_system_score_gemma":0.0007060367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003966971,"about_ca_topic_score_gemma":0.0003718487,"domain_scores_codex":[0.9935865,0.003514732,0.0002481559,0.0006239858,0.001672869,0.0003537429],"domain_scores_gemma":[0.9740013,0.0204565,0.0009313269,0.003231141,0.001073601,0.0003061192],"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":[0.0005987325,0.0002868325,0.003535397,0.00270299,0.0001021393,0.001192305,0.08179907,0.01083321,0.08093344,0.2751502,0.006430125,0.5364354],"study_design_scores_gemma":[0.0003152595,0.001494344,0.007677695,0.002985526,0.0003493146,0.004772175,0.02322632,0.05481856,0.1195987,0.2488393,0.5353842,0.0005386546],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1066376,0.002923664,0.8436792,0.001903808,0.0002201419,0.0003356919,0.0001438306,0.001677947,0.04247823],"genre_scores_gemma":[0.5833335,0.002045712,0.408264,0.0003131587,0.0001196966,0.0004367013,0.0001178822,0.0005018886,0.0048675],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.009218454,"threshold_uncertainty_score":0.03060037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03542419344704046,"score_gpt":0.3502342508792582,"score_spread":0.3148100574322177,"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."}}