{"id":"W2309145395","doi":"10.1007/978-3-319-24729-8_5","title":"The Rendezvous Problem: Limited Camera Range","year":2015,"lang":"en","type":"book-chapter","venue":"Springer briefs in electrical and computer engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rendezvous; Visibility; Computer science; Range (aeronautics); Computer vision; Graph; Lipschitz continuity; Artificial intelligence; Mathematics; Theoretical computer science; Engineering; Physics; Mathematical analysis; Optics","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":[0.0007074627,0.001338701,0.002375576,0.0006928638,0.0008941814,0.002733981,0.002730461,0.003124473,0.008513275],"category_scores_gemma":[0.003306639,0.0009790312,0.00079667,0.001409721,0.002274333,0.004637127,0.002873585,0.002268667,0.001389478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009422559,"about_ca_system_score_gemma":0.0006399964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002581319,"about_ca_topic_score_gemma":0.001567961,"domain_scores_codex":[0.9992174,0.0002024394,0.00002571803,0.0002842886,0.0001748179,0.00009525326],"domain_scores_gemma":[0.9990286,0.0006389142,0.00009559561,0.0001108109,0.00005202675,0.00007408913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000560767,0.00008764856,0.0004761397,0.001224462,0.0001644096,0.0008491055,0.0004164347,0.440384,0.0108244,0.4278659,0.0192588,0.09788808],"study_design_scores_gemma":[0.0001365135,0.0001221608,0.0006225367,0.0002050611,0.00006750093,0.001068462,0.0003770847,0.4978946,0.004298355,0.4670222,0.02807967,0.0001059144],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05587098,0.01806984,0.8192434,0.003165837,0.0005526973,0.0001166769,0.000816808,0.0005078531,0.1016559],"genre_scores_gemma":[0.7836403,0.01524082,0.1225556,0.0004964736,0.001023749,0.0002849769,0.0008315249,0.0006416436,0.07528497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008513275,"threshold_uncertainty_score":0.02847975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622149076531311,"score_gpt":0.209121553453279,"score_spread":0.1929000626879659,"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."}}