{"id":"W2812765312","doi":"10.1111/cgf.13425","title":"ThreadReconstructor: Modeling Reply‐Chains to Untangle Conversational Text through Visual Analytics","year":2018,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Software Engineering Research","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Heuristics; Visual analytics; Visualization; Analytics; Human–computer interaction; Data visualization; Artificial intelligence; Data science; Machine learning; Information retrieval","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":[0.003492261,0.001330295,0.0006471873,0.003896906,0.0006224242,0.003257888,0.001681618,0.001062518,0.00585717],"category_scores_gemma":[0.01457768,0.0006004955,0.001038225,0.001525628,0.0008808227,0.00295277,0.002230929,0.001417519,0.001618844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008636198,"about_ca_system_score_gemma":0.001136176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005267274,"about_ca_topic_score_gemma":0.005333761,"domain_scores_codex":[0.9985633,0.0006472957,0.00008484334,0.0003412395,0.0002644707,0.00009872251],"domain_scores_gemma":[0.991867,0.005798292,0.0006940124,0.0007483817,0.0005956027,0.0002966973],"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":[0.001942092,0.0005044584,0.02519611,0.001536443,0.0002632957,0.0006650246,0.01807559,0.1676039,0.0558469,0.05259868,0.02144224,0.6543252],"study_design_scores_gemma":[0.0000300627,0.00006190035,0.001497641,0.00007021001,0.00001736226,0.0000583929,0.0006320504,0.95952,0.008098783,0.02142819,0.00854338,0.00004205494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04204684,0.0002189065,0.9376605,0.0003036409,0.0000471016,0.0002044598,0.0014561,0.01663813,0.00142428],"genre_scores_gemma":[0.3089071,0.0001673454,0.6844537,0.00008164118,0.00003949439,0.0004232992,0.002547122,0.001817638,0.00156272],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00585717,"threshold_uncertainty_score":0.01959419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03116623171626524,"score_gpt":0.2922717656578509,"score_spread":0.2611055339415856,"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."}}