{"id":"W1499762049","doi":"10.4230/dfu.vol6.12191.21","title":"Pathfinding in Games","year":2013,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Pathfinding; Workgroup; Testbed; Computer science; Human–computer interaction; Toolbox; Artificial intelligence; World Wide Web; Shortest path problem; Theoretical computer science; Programming language","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005850031,0.0003639676,0.0004117773,0.0004557324,0.0002080913,0.0008232355,0.001860328,0.0002140058,0.0001065939],"category_scores_gemma":[0.0002088358,0.000331442,0.0001909398,0.0005759597,0.0001294764,0.003951806,0.0005879156,0.0004250897,0.001450097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001680532,"about_ca_system_score_gemma":0.0000774644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001212643,"about_ca_topic_score_gemma":0.00005189991,"domain_scores_codex":[0.996852,0.00004140338,0.001295424,0.0003390711,0.0004791901,0.0009929391],"domain_scores_gemma":[0.998027,0.000247618,0.0003490364,0.0009191427,0.0002478313,0.0002094323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005876827,0.001079145,0.102789,0.0007573256,0.0001848149,0.00003580471,0.0916035,0.001531975,0.000979768,0.1892116,0.02559732,0.586171],"study_design_scores_gemma":[0.001895553,0.0005085875,0.01221936,0.00053193,0.00001979604,0.0001011129,0.007815047,0.8378653,0.01673396,0.04299729,0.07729587,0.002016169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5497877,0.00007169833,0.4338468,0.00122323,0.001642462,0.00198156,0.00004750631,0.0004449099,0.01095413],"genre_scores_gemma":[0.9507595,0.00002707668,0.04707654,0.001248227,0.0001115417,0.0003123969,0.0000343248,0.00003262827,0.0003978086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8363333,"threshold_uncertainty_score":0.9999138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0205290463472283,"score_gpt":0.2652369112787808,"score_spread":0.2447078649315525,"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."}}