{"id":"W2805058177","doi":"10.1145/3205929.3205933","title":"GaRSIVis","year":2018,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Institute for Computing, Information and Cognitive Systems","keywords":"Computer science; Gaze; Visualization; Data visualization; Reading (process); Filter (signal processing); Human–computer interaction; Artificial intelligence; Data modeling; Machine learning; Data mining; Computer vision; Database","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006214113,0.00003147805,0.00004338507,0.0001132709,0.00007610422,0.0001725392,0.000306652,0.00001199316,0.01868779],"category_scores_gemma":[0.0001477493,0.00001948507,0.00003029793,0.0003000808,0.00004769204,0.0004008845,0.00006496225,0.00001633202,0.02536267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004359429,"about_ca_system_score_gemma":0.000005674905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004527657,"about_ca_topic_score_gemma":0.00001428291,"domain_scores_codex":[0.9991242,0.00001159655,0.000165034,0.00008944602,0.0005278066,0.00008195954],"domain_scores_gemma":[0.999507,0.00005333053,0.00003499958,0.00020065,0.0001674652,0.00003656623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005160412,0.000010988,0.01905939,1.752703e-7,0.000002039435,6.224597e-7,0.0004127519,3.268602e-7,0.00009709614,0.03589534,0.8403974,0.1041187],"study_design_scores_gemma":[0.00008621886,0.00002987892,0.1004684,5.665603e-7,0.000001824785,6.62567e-7,0.0005450469,0.001126751,0.0005676282,0.005880877,0.8912359,0.00005624331],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3758929,0.000001617671,0.00720741,0.001118428,0.0002190829,0.00003475842,7.741222e-7,0.00004357522,0.6154815],"genre_scores_gemma":[0.902109,3.038275e-7,0.000878521,0.001579662,0.00007909479,0.000001178046,4.612176e-7,0.000001123622,0.09535071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.526216,"threshold_uncertainty_score":0.9822093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.476069697491297,"score_gpt":0.5084823223662762,"score_spread":0.0324126248749792,"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."}}