{"id":"W1061820890","doi":"10.1007/s10878-015-9936-0","title":"Lower bounds for positive semidefinite zero forcing and their applications","year":2015,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Combinatorics; Vertex cover; Positive-definite matrix; Theory of computation; Vertex (graph theory); Zero (linguistics); Discrete mathematics; Graph; Forcing (mathematics); Semidefinite programming; Upper and lower bounds; Algorithm; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008693098,0.00009574161,0.0001782205,0.0001819959,0.0001347636,0.0001708949,0.0003462718,0.00005794096,6.981671e-7],"category_scores_gemma":[0.0002435857,0.0000797134,0.00006299618,0.0003572273,0.00006357171,0.0009516778,0.0000899092,0.0001317378,5.790991e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008393243,"about_ca_system_score_gemma":0.0001578404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.750591e-7,"about_ca_topic_score_gemma":5.584434e-8,"domain_scores_codex":[0.9991074,0.00007555647,0.0002948085,0.0001334471,0.0002297394,0.0001590525],"domain_scores_gemma":[0.9979289,0.0003073178,0.0002991594,0.0001732945,0.001131385,0.0001599288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002993879,0.0001430152,0.00005911406,0.0000123354,0.00005122606,0.00000278559,0.0008884551,0.1112421,0.0002794772,0.8806314,0.0005108903,0.005879752],"study_design_scores_gemma":[0.002287123,0.0008064778,0.000009858778,0.00003216886,0.00001160204,0.00004981288,0.00006819831,0.148443,0.001146654,0.8445807,0.002429065,0.0001353811],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005200672,0.0002194151,0.9972149,0.000425598,0.0009866639,0.000277026,0.000003236189,0.00001833878,0.0003347224],"genre_scores_gemma":[0.6213281,0.00005172363,0.3780721,0.00009549541,0.000349629,0.00003072392,0.000005165243,0.00002056198,0.00004653674],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.620808,"threshold_uncertainty_score":0.3250618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974725460452239,"score_gpt":0.2832249792297368,"score_spread":0.2634777246252145,"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."}}