{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005734058,0.000493578,0.0004939301,0.001057278,0.0003753303,0.00079963,0.003569853,0.0002464037,0.0001898467],"category_scores_gemma":[0.00006560044,0.0004842653,0.0001553736,0.0008193222,0.0009840291,0.0006627976,0.001562026,0.0004703944,0.0002431688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002900103,"about_ca_system_score_gemma":0.0005018344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007598567,"about_ca_topic_score_gemma":0.00003466783,"domain_scores_codex":[0.9961095,0.00003309382,0.0006380543,0.001427934,0.001216713,0.0005746816],"domain_scores_gemma":[0.9973197,0.000215559,0.0004075048,0.001220185,0.0006138396,0.0002231858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001422907,0.0003148204,0.0003480782,0.0001608009,0.0001859834,0.0003875291,0.003856638,0.1970855,0.0002168996,0.6071632,0.004807408,0.1854589],"study_design_scores_gemma":[0.0003119714,0.0001429209,0.00006651477,0.0002031781,0.00001330093,0.00003127014,3.62413e-7,0.7945189,0.0002118209,0.2001557,0.003775091,0.0005689011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002793416,0.00007156083,0.9937983,0.0004657611,0.001010622,0.0002048366,0.00002719125,0.0001041712,0.00428963],"genre_scores_gemma":[0.1925798,0.00007031856,0.7884995,0.01137273,0.001947714,0.000007072153,0.0004031021,0.0001313954,0.004988386],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5974334,"threshold_uncertainty_score":0.9997609,"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."}}