{"id":"W1640718621","doi":"","title":"BoRK or BT? An Analysis for Vayne Players in League of Legends","year":2014,"lang":"en","type":"article","venue":"Journal of Interdisciplinary Science Topics","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"League; Armour; Advertising; Game play; Engineering; Operations research; History; Computer science; Business; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009562114,0.0003673086,0.0005284884,0.0007388766,0.0007667384,0.001720507,0.0007470527,0.001005073,0.01580875],"category_scores_gemma":[0.004888281,0.0002211373,0.0005692627,0.0005254211,0.0004390665,0.0008638416,0.0007589314,0.001398389,0.001623906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120402,"about_ca_system_score_gemma":0.0004622045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02817157,"about_ca_topic_score_gemma":0.06226151,"domain_scores_codex":[0.9994251,0.0001628442,0.00002735644,0.0001008996,0.00006625025,0.0002175959],"domain_scores_gemma":[0.9961032,0.002648868,0.0004293959,0.00008736321,0.0002433502,0.00048797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01022168,0.003147732,0.8953597,0.0003563426,0.000511162,0.001501326,0.004062208,0.02015057,0.004508378,0.01277527,0.008146551,0.03925906],"study_design_scores_gemma":[0.0001456305,0.002415577,0.9193225,0.00008281064,0.0002159515,0.0004897596,0.02480218,0.04301678,0.000975166,0.003631359,0.004829874,0.00007242311],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955434,0.0001088247,0.0004135785,0.0001800023,0.000009479118,0.0000251047,0.0005050821,0.000005015202,0.003209572],"genre_scores_gemma":[0.9947607,0.00005090114,0.0002141892,0.00003198035,0.000005910684,0.00001499971,0.0006938715,0.000007006223,0.004220543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02817157,"threshold_uncertainty_score":0.05601519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03525023317836615,"score_gpt":0.3862517540008413,"score_spread":0.3510015208224752,"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."}}