{"id":"W1519709295","doi":"10.1007/978-3-642-36763-2_25","title":"Kinetic and Stationary Point-Set Embeddability for Plane Graphs","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Mathematics; Combinatorics; Plane (geometry); Time complexity; Embedding; Graph; Function (biology); Algebraic number; Discrete mathematics; Geometry; Mathematical analysis; Computer science","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":[0.0002605968,0.0006904267,0.0006565981,0.001530905,0.0007154553,0.001889383,0.001197543,0.0009193404,0.007534027],"category_scores_gemma":[0.001771632,0.0004898811,0.0007484683,0.001023283,0.00172032,0.002864907,0.001405985,0.002308299,0.001012226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005850568,"about_ca_system_score_gemma":0.0002019108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006467745,"about_ca_topic_score_gemma":0.0005364494,"domain_scores_codex":[0.9997687,0.00003751503,0.00001290218,0.00005726653,0.00008939912,0.00003430332],"domain_scores_gemma":[0.9992842,0.000335323,0.0001063744,0.0001024078,0.00008028416,0.00009137924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003566344,0.00002176622,0.0001917474,0.00007087641,0.000009131986,0.00008336377,0.0002160981,0.0108218,0.002519682,0.9751012,0.001296235,0.009632524],"study_design_scores_gemma":[0.0000117762,0.00001633437,0.000188362,0.00001559624,0.000006458185,0.0001174386,0.000095667,0.03003832,0.0008429752,0.9665543,0.002102041,0.00001063017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4205699,0.001744819,0.4531782,0.001242082,0.000248691,0.0001049445,0.0007058523,0.0004095437,0.1217961],"genre_scores_gemma":[0.9187113,0.001693527,0.03591147,0.0001513187,0.0002358144,0.0001125743,0.0008535856,0.000333779,0.04199657],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007534027,"threshold_uncertainty_score":0.02520382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684277568243483,"score_gpt":0.2504623982825729,"score_spread":0.233619622600138,"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."}}