{"id":"W3083632304","doi":"10.1109/vis47514.2020.00023","title":"Designing for Ambiguity: Visual Analytics in Avalanche Forecasting","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University","keywords":"Sensemaking; Ambiguity; Visual analytics; Data science; Computer science; Variety (cybernetics); Visualization; Analytics; Negotiation; Domain (mathematical analysis); Knowledge management; Management science; Artificial intelligence; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0006034977,0.0002505829,0.0004257144,0.000252841,0.00006343949,0.0005737027,0.001171093,0.0001792766,0.00001050084],"category_scores_gemma":[0.0004888349,0.0002538065,0.0001447016,0.0005126416,0.00001374054,0.0002079606,0.00179911,0.0003393632,0.00001249054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001552341,"about_ca_system_score_gemma":0.0002524559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006540646,"about_ca_topic_score_gemma":0.00006791371,"domain_scores_codex":[0.998032,0.00006139652,0.0005557296,0.0007293813,0.0002832568,0.000338216],"domain_scores_gemma":[0.998863,0.0001814766,0.0002432234,0.0004433289,0.0001371844,0.00013176],"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":[0.00008897659,0.001389368,0.02654809,0.005480039,0.000860805,0.0004263883,0.00754276,0.1344353,0.001734665,0.4320344,0.1467268,0.2427324],"study_design_scores_gemma":[0.0002639648,0.00004288362,0.00007090557,0.0001122104,0.00001828516,0.000001681411,0.00004701805,0.9855064,0.0007531263,0.01119981,0.001683066,0.0003007138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002255702,0.00002672099,0.9961942,0.001473622,0.0003257522,0.0003310628,0.00001527794,0.000216552,0.0011912],"genre_scores_gemma":[0.2561655,0.00003596799,0.7394935,0.002664512,0.0003374468,0.0000540654,0.0002825343,0.00004732361,0.0009192007],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8510711,"threshold_uncertainty_score":0.9999914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.154398369162422,"score_gpt":0.3603589449248796,"score_spread":0.2059605757624577,"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."}}