{"id":"W1556720455","doi":"10.48550/arxiv.1303.2162","title":"New Hardness Results for Guarding Orthogonal Polygons with Sliding Cameras","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cardinality (data modeling); Combinatorics; Point (geometry); Line segment; Guard (computer science); Polygon (computer graphics); Set (abstract data type); Time complexity; Regular polygon; Mathematics; Computer science; Geometry","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":[0.0009401799,0.001220262,0.001168426,0.0007304132,0.001323561,0.002577711,0.002583305,0.001726218,0.01025593],"category_scores_gemma":[0.007708913,0.0009413568,0.002008346,0.001448337,0.001996592,0.008574842,0.003716929,0.004088236,0.0009084157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001526946,"about_ca_system_score_gemma":0.001222828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00335365,"about_ca_topic_score_gemma":0.003616673,"domain_scores_codex":[0.998399,0.0003258131,0.0001039863,0.0004294492,0.0004309002,0.0003108783],"domain_scores_gemma":[0.9942324,0.003988517,0.0005400587,0.0007515444,0.0002062092,0.0002812139],"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":[0.0006961319,0.0004032419,0.005421305,0.001555103,0.0001755932,0.0008723701,0.00123581,0.3553775,0.007554837,0.4822276,0.03786415,0.1066164],"study_design_scores_gemma":[0.0001615576,0.0001453889,0.001412269,0.0001111858,0.00008339304,0.0005559236,0.0005098232,0.4254727,0.003068202,0.549145,0.01928391,0.00005067893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1861204,0.001882122,0.7546688,0.007080497,0.0003200844,0.0003672961,0.004368475,0.001457764,0.04373458],"genre_scores_gemma":[0.7094086,0.001982894,0.2672116,0.001062907,0.0005009481,0.0004777664,0.005369514,0.0006306259,0.01335513],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01025593,"threshold_uncertainty_score":0.03430951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07851725886197111,"score_gpt":0.196664348701574,"score_spread":0.1181470898396029,"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."}}