{"id":"W2578871007","doi":"","title":"Optimum Seating Arrangements and Tuscan Squares.","year":2016,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Least-squares function approximation; Statistics","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":[0.0002721069,0.0006782932,0.0006770829,0.0008742336,0.0007244915,0.0009995493,0.0007661175,0.001029262,0.04628602],"category_scores_gemma":[0.002361518,0.0004214449,0.0003939059,0.001304286,0.0008658837,0.00121314,0.001209234,0.001028719,0.002946598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001105872,"about_ca_system_score_gemma":0.0007009883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00492713,"about_ca_topic_score_gemma":0.008364148,"domain_scores_codex":[0.9997182,0.0001004757,0.000007787932,0.00004558659,0.00005252292,0.0000753581],"domain_scores_gemma":[0.9997212,0.0001272394,0.00004458681,0.00002662303,0.00003165407,0.00004858285],"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":[0.0006997635,0.0001270127,0.001470112,0.0003106955,0.00004557302,0.0001970363,0.0001775346,0.2597021,0.002950829,0.5733264,0.03637054,0.1246225],"study_design_scores_gemma":[0.0001648657,0.0002344417,0.003601433,0.0001310286,0.00004207816,0.0003123142,0.0003342843,0.4067103,0.002393112,0.5394778,0.04655474,0.00004360394],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3029341,0.002650663,0.3203405,0.001786522,0.0005200857,0.0001863766,0.002118534,0.0006879906,0.3687752],"genre_scores_gemma":[0.7633843,0.001449301,0.08370896,0.0001999461,0.0001296417,0.0001666759,0.001600041,0.0002116128,0.1491494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04628602,"threshold_uncertainty_score":0.1548421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008008780175602014,"score_gpt":0.2084658774796507,"score_spread":0.2004570973040487,"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."}}