{"id":"W2171410117","doi":"10.5614/ejgta.2015.3.1.2","title":"On scores, losing scores and total scores in hypertournaments","year":2015,"lang":"en","type":"article","venue":"Electronic Journal of Graph Theory and Applications","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Killam Trusts; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Combinatorics; Mathematics; Hypergraph; Element (criminal law); Vertex (graph theory); Enhanced Data Rates for GSM Evolution; Graph; Computer science; Artificial intelligence; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003561786,0.001662209,0.001369246,0.003322499,0.002269967,0.004760013,0.002440457,0.001640874,0.009965912],"category_scores_gemma":[0.0240314,0.0005924916,0.00102263,0.003765153,0.006180052,0.009685421,0.003474643,0.003111303,0.001123132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002522662,"about_ca_system_score_gemma":0.001011455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001861023,"about_ca_topic_score_gemma":0.002247321,"domain_scores_codex":[0.9951622,0.001314004,0.0003412074,0.001018431,0.001094914,0.0010694],"domain_scores_gemma":[0.9765817,0.01428317,0.002940326,0.001521924,0.001772471,0.00290036],"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":[0.0002576729,0.0000898774,0.004515249,0.0001424053,0.00005031603,0.0001768295,0.0005840528,0.01757191,0.001764119,0.9425992,0.002369879,0.02987848],"study_design_scores_gemma":[0.00003260291,0.0001497648,0.00233113,0.00005990831,0.00003787616,0.0001951481,0.0002711149,0.04678629,0.0009203004,0.946114,0.003059085,0.00004284905],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6118246,0.00135561,0.3204967,0.001829408,0.0002466252,0.0001675216,0.001231181,0.0004122707,0.06243606],"genre_scores_gemma":[0.9427965,0.0007545587,0.0416722,0.0003163873,0.0003604611,0.000301595,0.001180666,0.0002471287,0.01237055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009965912,"threshold_uncertainty_score":0.03333932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486821573934679,"score_gpt":0.2869802082873247,"score_spread":0.272111992547978,"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."}}