{"id":"W201798103","doi":"10.1007/978-3-319-07557-0_16","title":"A $\\frac{5}{4}$ -Approximation for Subcubic 2EC Using Circulations","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Mathematics; Combinatorics; Approximation algorithm; Integer (computer science); Relaxation (psychology); Linear programming relaxation; Discrete mathematics; Linear programming; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001059237,0.0004892318,0.0005295448,0.001070583,0.0006098611,0.000695966,0.002681717,0.000309368,0.00001326282],"category_scores_gemma":[0.0001336374,0.0004972179,0.000247343,0.0007600544,0.0005679118,0.0005754724,0.0007878967,0.0005202558,0.00001519425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003009681,"about_ca_system_score_gemma":0.0004749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002191183,"about_ca_topic_score_gemma":0.00004467048,"domain_scores_codex":[0.9964359,0.000036341,0.0005930784,0.001469805,0.0008020084,0.0006628601],"domain_scores_gemma":[0.9969804,0.0007127201,0.0003651755,0.001409941,0.0003800211,0.0001517908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003679255,0.0000260646,0.00001821418,0.00008276691,0.00001475737,0.000007313758,0.0004997074,0.06420109,0.0001934364,0.2926229,0.00001461724,0.6423154],"study_design_scores_gemma":[0.0001707393,0.00006459939,0.00003083285,0.0001651712,0.000008786669,0.00003609671,5.901289e-8,0.6346477,0.0001798332,0.3632085,0.001104998,0.0003826104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007651486,0.0001916371,0.9956025,0.0004621806,0.001963526,0.000729183,0.00001092543,0.0001966031,0.0007669286],"genre_scores_gemma":[0.06841906,0.000006654768,0.9298554,0.0007834013,0.0007155701,0.00002254047,0.00001583249,0.00003810461,0.0001433971],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6419328,"threshold_uncertainty_score":0.9997479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04149496949630287,"score_gpt":0.2730944437374828,"score_spread":0.2315994742411799,"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."}}