{"id":"W2050995286","doi":"10.1117/12.872578","title":"EdgeMaps: visualizing explicit and implicit relations","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Computer science; Visualization; Graph drawing; Focus (optics); Theoretical computer science; GRASP; Graph; Spatialization; Node (physics); Similarity (geometry); Data visualization; Information visualization; Human–computer interaction; Artificial intelligence; 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":[0.0015789,0.001235644,0.000680601,0.00428448,0.0006119556,0.003205633,0.001168875,0.001047391,0.008295308],"category_scores_gemma":[0.008495496,0.0005304372,0.000703321,0.003996849,0.0004803192,0.00594797,0.003100835,0.001591143,0.00142194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003156728,"about_ca_system_score_gemma":0.0007121192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001749887,"about_ca_topic_score_gemma":0.002830653,"domain_scores_codex":[0.9993033,0.0002188083,0.00005814271,0.0001106762,0.0002552661,0.00005370147],"domain_scores_gemma":[0.996161,0.002491504,0.0002467403,0.0004222524,0.0005133494,0.0001651148],"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":[0.001001034,0.0002567411,0.007766935,0.002946417,0.0002512568,0.001028431,0.007160727,0.03053724,0.0389286,0.09768804,0.08277966,0.7296549],"study_design_scores_gemma":[0.0002135102,0.0002280673,0.007711022,0.0007991129,0.0001843658,0.001331455,0.002807124,0.3233818,0.04459554,0.2243399,0.3940551,0.0003528847],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02524507,0.001017326,0.9495364,0.0009666196,0.0003038869,0.0001968354,0.005073881,0.01211991,0.005540157],"genre_scores_gemma":[0.1326092,0.001344741,0.8543893,0.0003494833,0.0001020995,0.0004516728,0.005722015,0.002185433,0.002846101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008295308,"threshold_uncertainty_score":0.02775055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375671249526078,"score_gpt":0.2606639013599253,"score_spread":0.2369071888646646,"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."}}