{"id":"W2952911535","doi":"10.48550/arxiv.1407.1428","title":"Fast Rendezvous with Advice","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Advice (programming); Psychology; Computer science; Engineering; Aerospace engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002132724,0.0002522024,0.000249569,0.0002214511,0.0001463237,0.0001885386,0.001834276,0.0001888317,0.00005534686],"category_scores_gemma":[0.00001502612,0.0002498381,0.00009061191,0.000537335,0.0000964071,0.0003125388,0.001494024,0.0005255936,0.0001825753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057319,"about_ca_system_score_gemma":0.0002205817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009462624,"about_ca_topic_score_gemma":0.00005534881,"domain_scores_codex":[0.9982657,0.0001525466,0.0001346819,0.0009714763,0.0001298358,0.0003457799],"domain_scores_gemma":[0.9980243,0.0000579632,0.0001783711,0.001281243,0.0002387405,0.0002194156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001690102,0.00005239485,0.0005834975,0.0000523795,0.00004578064,0.0001338298,0.0001989938,0.8589426,0.000002372912,0.1382552,0.0009148326,0.0008011864],"study_design_scores_gemma":[0.0004743911,0.00009302147,0.0002790459,0.00007461883,0.00002034924,0.000007442487,0.00002752836,0.9885262,0.00001610648,0.007245585,0.002851056,0.0003846553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005536166,0.00001382443,0.9655641,0.0002308236,0.0002121715,0.000225838,0.00000458109,0.0005259428,0.02768655],"genre_scores_gemma":[0.9734489,0.00007654494,0.0171685,0.0002559734,0.00005031579,0.00000105294,0.0000156968,0.0000190796,0.008963932],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9679127,"threshold_uncertainty_score":0.9999954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04878298937957758,"score_gpt":0.1774679760883414,"score_spread":0.1286849867087638,"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."}}