{"id":"W2026309121","doi":"10.1145/2559206.2580934","title":"Sisyphorest","year":2014,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visualization; Term (time); BitTorrent tracker; Informatics; Human–computer interaction; Artificial intelligence; Engineering; Eye tracking","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":[0.0008697524,0.001309147,0.0008228104,0.001113328,0.0006591106,0.001910844,0.002265995,0.0009588228,0.06947184],"category_scores_gemma":[0.003242745,0.0006477402,0.0008217864,0.0007444024,0.0005572147,0.003119972,0.003754156,0.001539553,0.03058667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005813999,"about_ca_system_score_gemma":0.00155506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003007947,"about_ca_topic_score_gemma":0.003521735,"domain_scores_codex":[0.9992065,0.0001018074,0.0000497826,0.0002035744,0.0003583811,0.00008000826],"domain_scores_gemma":[0.9985718,0.0003676994,0.00006608588,0.000481032,0.0003516542,0.0001618415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002740218,0.0005619114,0.005326721,0.001351698,0.0001610342,0.000502277,0.001200894,0.00395853,0.0152162,0.02316803,0.4560703,0.4897421],"study_design_scores_gemma":[0.0004721595,0.0007920841,0.005782643,0.0002328006,0.0001364459,0.001049206,0.0002307304,0.03859335,0.01744897,0.01717437,0.9178928,0.0001944372],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"other","genre_scores_codex":[0.03278798,0.001766793,0.2856936,0.001434856,0.001038012,0.001656978,0.02410593,0.4155838,0.235932],"genre_scores_gemma":[0.2207043,0.00209169,0.3622627,0.002340021,0.0003196176,0.002745656,0.06422164,0.02918937,0.3161249],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06947184,"threshold_uncertainty_score":0.2324064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007273180406618784,"score_gpt":0.2285740290075898,"score_spread":0.221300848600971,"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."}}