{"id":"W2406120758","doi":"","title":"A Note on Upper Generalized Exponents of Tournaments.","year":2014,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Combinatorics; Pure mathematics; Mathematical economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001887617,0.001186321,0.001183847,0.002202244,0.002043666,0.004468611,0.001469095,0.001277555,0.01763286],"category_scores_gemma":[0.0106303,0.0005142983,0.001369882,0.002256971,0.003976147,0.007570767,0.00349294,0.007243605,0.003170114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001346112,"about_ca_system_score_gemma":0.0005759562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014377,"about_ca_topic_score_gemma":0.00138586,"domain_scores_codex":[0.9984134,0.0004621151,0.0001009399,0.0003116602,0.0004301567,0.0002817122],"domain_scores_gemma":[0.9940264,0.00388893,0.0002959017,0.00076959,0.0005324067,0.000486785],"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":[0.00003572478,0.00001325638,0.000209901,0.00005945599,0.000007901659,0.0001094739,0.0001165803,0.0005320133,0.0004446441,0.9875433,0.004117562,0.00681014],"study_design_scores_gemma":[0.0000134935,0.00001890599,0.0002327235,0.00003949286,0.000009668806,0.0001380863,0.00004388102,0.001975216,0.0002380682,0.9809823,0.01629498,0.00001319058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1081402,0.0145579,0.264136,0.01251753,0.005874166,0.000128196,0.0009678232,0.0005622525,0.5931159],"genre_scores_gemma":[0.8219108,0.008976077,0.08028306,0.004766576,0.005203069,0.0002223516,0.0005811637,0.0005847535,0.07747214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01763286,"threshold_uncertainty_score":0.05898774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02284113028664316,"score_gpt":0.2829236461014747,"score_spread":0.2600825158148315,"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."}}