{"id":"W2576239431","doi":"","title":"Action selection for hammer shots in curling","year":2016,"lang":"en","type":"article","venue":"International Joint Conference on Artificial Intelligence","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Delaunay triangulation; Curling; Hammer; Computer science; Action (physics); Selection (genetic algorithm); Artificial intelligence; State space; Triangulation; Computer vision; Mathematical optimization; Algorithm; Mathematics; Engineering; Geometry; Statistics; Structural engineering; Mechanical engineering; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003361085,0.0001951641,0.0001729439,0.0003635285,0.00009368579,0.0002907247,0.0007606802,0.00009713192,0.0002415912],"category_scores_gemma":[0.0002905425,0.0001509366,0.0000858426,0.0003079616,0.00006359111,0.0008362359,0.00008793987,0.000148444,0.0002690715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001866038,"about_ca_system_score_gemma":0.0001592043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006450654,"about_ca_topic_score_gemma":0.0003666283,"domain_scores_codex":[0.9981022,0.00003920148,0.0005392948,0.0006114038,0.0003634041,0.0003444385],"domain_scores_gemma":[0.9988975,0.0001703138,0.0001871145,0.0002328288,0.000427153,0.00008508457],"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":[0.000036578,0.00007683483,0.0001406096,0.000005127222,0.000006450133,0.000001892797,0.0001079247,0.00008195061,0.01785287,0.5899582,0.00004730385,0.3916843],"study_design_scores_gemma":[0.000110842,0.0002277107,0.0008452256,0.0003260554,0.000002974579,0.00001482402,0.00009111226,0.2148276,0.2495158,0.5321574,0.001515343,0.0003650164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008219464,0.000004566833,0.9761778,0.01126165,0.001348821,0.0002426748,0.000007795823,0.000110592,0.002626624],"genre_scores_gemma":[0.9871933,0.00005469407,0.01181157,0.0003018421,0.0001945051,0.00010081,0.000002667587,0.00001073542,0.0003298927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9789738,"threshold_uncertainty_score":0.6155018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1744397893897128,"score_gpt":0.359484580898046,"score_spread":0.1850447915083333,"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."}}