{"id":"W2896743066","doi":"10.1007/978-3-030-01388-2_5","title":"Immersive Human-Centered Computational Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Analytics; Human–computer interaction; Computer graphics (images); Data science","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":[0.0005098736,0.001377066,0.0005808959,0.0003498249,0.0003604866,0.002377417,0.001597519,0.0007941706,0.03063147],"category_scores_gemma":[0.001493558,0.0005906749,0.0006565089,0.0003711665,0.001254072,0.002383855,0.004957418,0.001718009,0.003542869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000187037,"about_ca_system_score_gemma":0.0003482193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000578474,"about_ca_topic_score_gemma":0.001323776,"domain_scores_codex":[0.9996262,0.000111392,0.00001058478,0.00007043618,0.0001449331,0.00003653717],"domain_scores_gemma":[0.9992823,0.0004408148,0.00001837897,0.0001177751,0.00007288488,0.00006791765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003187719,0.0003415458,0.0008650657,0.002214269,0.0002540696,0.0005321372,0.004278553,0.05833344,0.08183273,0.2342458,0.1066623,0.5101212],"study_design_scores_gemma":[0.00009177266,0.0002994077,0.001850546,0.000832259,0.00008166867,0.001101203,0.001405248,0.1596585,0.03348469,0.2696033,0.5314182,0.0001732813],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006426017,0.002655142,0.9500563,0.0005570378,0.000529828,0.00006252406,0.0004170493,0.002793757,0.03650245],"genre_scores_gemma":[0.1904367,0.008583281,0.7076311,0.0008725269,0.0004908453,0.0004411901,0.002134971,0.001534052,0.08787541],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03063147,"threshold_uncertainty_score":0.1024725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03971296169331512,"score_gpt":0.311849106838917,"score_spread":0.2721361451456019,"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."}}