{"id":"W2592594462","doi":"10.1145/3038462.3038469","title":"Active Learning with Visualization for Text Data","year":2017,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Active learning (machine learning); Visualization; Bottleneck; Learning analytics; Machine learning; Artificial intelligence; Semi-supervised learning; Visual analytics; Interface (matter); Interactive Learning; Interactive visualization; Data visualization; Annotation; Analytics; Data mining; Multimedia","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":[],"consensus_categories":[],"category_scores_codex":[0.0001860498,0.00005794916,0.00006342235,0.00002276645,0.0005889249,0.0004172386,0.001247882,0.00001801555,0.00001189737],"category_scores_gemma":[0.0001847493,0.000041114,0.000009356025,0.00003280511,0.00002087119,0.0008329838,0.0003869577,0.0000708369,0.00001562547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005138747,"about_ca_system_score_gemma":0.0000267374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000806656,"about_ca_topic_score_gemma":0.00001727413,"domain_scores_codex":[0.9994296,0.00002059549,0.00005072871,0.0002804648,0.0001017757,0.0001168809],"domain_scores_gemma":[0.998903,0.00005195175,0.00009691317,0.0008674133,0.00004891743,0.00003177502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001794967,0.00003738284,0.004017451,0.0000140539,0.00002738046,0.000002920583,0.0005617471,0.0007357018,0.00007882598,0.08419331,0.001459277,0.908854],"study_design_scores_gemma":[0.0003130983,0.0001148888,0.004787827,0.000009989622,0.000003215571,0.00000330581,0.00002622833,0.9625517,0.0002999241,0.0002738767,0.03152346,0.00009250618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001152553,0.000003654313,0.9880331,0.0007838975,0.00007973813,0.00008330587,0.0000013629,0.000125385,0.009737044],"genre_scores_gemma":[0.8233185,0.000003051673,0.1666133,0.0001176457,0.0001514221,0.000009418709,0.00003936236,0.00001111488,0.009736193],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.961816,"threshold_uncertainty_score":0.4529594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04228460451045758,"score_gpt":0.3515716966424781,"score_spread":0.3092870921320205,"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."}}