{"id":"W2951101008","doi":"10.48550/arxiv.1410.8756","title":"Contraction Obstructions for Connected Graph Searching","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mitacs; University of British Columbia","funders":"","keywords":"Monotone polygon; Mathematics; Combinatorics; Connected component; Finite set; Bounded function; Contraction (grammar); Strongly connected component; Graph; Discrete mathematics; Mixed graph; Induced subgraph; Line graph; Voltage graph","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":[0.0003451365,0.0001960906,0.0002335099,0.0003539353,0.0003627684,0.0002311315,0.0009618686,0.0002147832,0.00002377676],"category_scores_gemma":[0.0001174189,0.0002330363,0.0001988569,0.00043709,0.00008082564,0.0003999714,0.0005466249,0.0004946027,0.00002724244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001182832,"about_ca_system_score_gemma":0.0001614513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007800052,"about_ca_topic_score_gemma":0.00003347091,"domain_scores_codex":[0.9984257,0.0001857493,0.0001758711,0.0007901303,0.00008608084,0.0003364451],"domain_scores_gemma":[0.9982302,0.0002921824,0.0001916668,0.0007277682,0.0003798363,0.0001783252],"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":[0.00001493009,0.00003600739,0.0001483842,0.00005314611,0.00005637571,0.000006747053,0.0001028541,0.5749174,0.00005056542,0.423351,0.0003331311,0.0009295651],"study_design_scores_gemma":[0.0005720612,0.00004293852,0.0002894861,0.00003567813,0.00002303956,0.000003118749,0.00003211588,0.8919591,0.00005833347,0.1050979,0.001640521,0.0002456337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01864224,0.00001082704,0.977811,0.000287019,0.0008054062,0.00060056,0.0000190289,0.000381343,0.001442567],"genre_scores_gemma":[0.9811389,0.00007592215,0.01741279,0.0001000959,0.00008318785,0.000005037549,0.000053223,0.00001602922,0.001114761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9624967,"threshold_uncertainty_score":0.9502943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08985249067486402,"score_gpt":0.212596372958487,"score_spread":0.122743882283623,"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."}}