{"id":"W2107945074","doi":"10.1016/j.ipl.2006.06.015","title":"On the All-Farthest-Segments problem for a planar set of points","year":2006,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Set (abstract data type); Planar; Combinatorics; Computer science; Mathematics; Computational geometry; Algorithm; Computer graphics (images); Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003076537,0.00007550915,0.00006331121,0.0001224147,0.0001237638,0.0001688948,0.0002536348,0.00002195791,0.000002306219],"category_scores_gemma":[0.00002871524,0.00005577386,0.00003217722,0.0002272279,0.00001923712,0.001145037,0.00001741955,0.00004352704,0.00001796019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002360707,"about_ca_system_score_gemma":0.00004159663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005030331,"about_ca_topic_score_gemma":6.833417e-7,"domain_scores_codex":[0.9992375,0.00001860865,0.0002862646,0.00008285642,0.0002551738,0.0001195904],"domain_scores_gemma":[0.9994223,0.000105661,0.0002334977,0.0001166363,0.0001063766,0.00001554032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001083107,0.0001299585,0.0002056332,0.0005448811,0.00005878915,0.000001088743,0.007675482,0.1426451,0.009320333,0.4819097,0.1283145,0.2290862],"study_design_scores_gemma":[0.002425703,0.0003182938,0.002997676,0.0003028616,0.00002810937,0.00002831412,0.0001437808,0.7398568,0.04038079,0.1217855,0.09106502,0.0006672223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05577536,0.000007170423,0.9289739,0.01411476,0.00008124109,0.0002942042,0.000008423298,0.00004926055,0.0006956568],"genre_scores_gemma":[0.9088579,4.610666e-7,0.07674341,0.01410056,0.00007077986,0.00006318129,0.0001205555,0.000004482361,0.00003868379],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8530825,"threshold_uncertainty_score":0.2274392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01560613353605302,"score_gpt":0.2338658622227816,"score_spread":0.2182597286867285,"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."}}