{"id":"W2133860801","doi":"10.1145/1936652.1936673","title":"A set of multi-touch graph interaction techniques","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Graph; Set (abstract data type); Theoretical computer science; Human–computer interaction; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001284348,0.001968045,0.001153557,0.002921903,0.001144151,0.002383518,0.002185476,0.001470484,0.01853599],"category_scores_gemma":[0.005568454,0.0008796175,0.002993671,0.002669227,0.0007225757,0.003277932,0.004172473,0.002557429,0.003570019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244733,"about_ca_system_score_gemma":0.00054091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008709084,"about_ca_topic_score_gemma":0.001653219,"domain_scores_codex":[0.9974723,0.0005954676,0.0001641307,0.0003708958,0.001279673,0.0001174396],"domain_scores_gemma":[0.9967483,0.001562402,0.0001587307,0.0008166532,0.0005587154,0.0001551244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003179628,0.0002236575,0.0008993435,0.001287408,0.000222123,0.0004764876,0.001337421,0.01530914,0.07761959,0.03486074,0.02168521,0.8457609],"study_design_scores_gemma":[0.0002377855,0.0007392904,0.003226005,0.0006335978,0.0003483586,0.003574041,0.00107477,0.5254753,0.1197665,0.09216436,0.2523801,0.000379809],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001643968,0.0002516865,0.9906357,0.00008125496,0.00003783943,0.0001267,0.0002190042,0.00402497,0.002978864],"genre_scores_gemma":[0.03084231,0.0004867115,0.9623063,0.0001192253,0.00004807033,0.0004465966,0.0005544694,0.00109972,0.004096617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01853599,"threshold_uncertainty_score":0.0620091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0353864331781036,"score_gpt":0.3582446998680682,"score_spread":0.3228582666899646,"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."}}