{"id":"W2144129085","doi":"10.1109/tvcg.2006.127","title":"Composite Rectilinear Deformation for Stretch and Squish Navigation","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Deformation (meteorology); Computer science; Composite number; Computer graphics (images); Engineering drawing; Artificial intelligence; Computer vision; Composite material; Materials science; Engineering; Algorithm","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":[0.0005011881,0.0008687638,0.0007543467,0.000594803,0.0005555458,0.000736888,0.001100358,0.0006758019,0.007358567],"category_scores_gemma":[0.002008812,0.0004199128,0.0007787198,0.000918642,0.0006225452,0.001553373,0.002045562,0.0009655994,0.002314999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003890585,"about_ca_system_score_gemma":0.0008392908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003846021,"about_ca_topic_score_gemma":0.007609952,"domain_scores_codex":[0.9995079,0.00004338288,0.00003259603,0.0001674445,0.0002013849,0.00004722655],"domain_scores_gemma":[0.9993113,0.0001639452,0.000060255,0.0002962505,0.0001218828,0.00004627972],"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":[0.0005420449,0.0001161714,0.00220853,0.0001781578,0.00006439917,0.0001745969,0.0004442389,0.09899662,0.06609167,0.02126179,0.01546807,0.7944537],"study_design_scores_gemma":[0.00007136251,0.0002170097,0.001122133,0.00002793887,0.00002110063,0.000300827,0.0001329411,0.911302,0.03307825,0.01902853,0.03462039,0.00007747584],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0113171,0.00008879918,0.9829758,0.00007028803,0.00005120405,0.0000574164,0.0001408524,0.003758383,0.001540279],"genre_scores_gemma":[0.09122013,0.00008242553,0.9029378,0.00008025472,0.00002249744,0.0001229942,0.0007285,0.0007711533,0.004034291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007358567,"threshold_uncertainty_score":0.0246169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097537581388076,"score_gpt":0.2657442022131596,"score_spread":0.2547688263992788,"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."}}