{"id":"W2903783315","doi":"10.1145/3284432.3284464","title":"Getting to know Pepper","year":2018,"lang":"en","type":"article","venue":"","topic":"Cognitive Science and Education Research","field":"Neuroscience","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Engineering and Physical Sciences Research Council; European Commission","keywords":"Pepper; Computer science; Computer security","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":[0.001211235,0.0003884949,0.0001902115,0.0003514132,0.001155635,0.001904937,0.0003042578,0.0008881912,0.02570307],"category_scores_gemma":[0.009749445,0.0002083349,0.0002884334,0.0001548386,0.0007699747,0.004138949,0.001689766,0.001030252,0.005898801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004781252,"about_ca_system_score_gemma":0.0003766149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001088922,"about_ca_topic_score_gemma":0.001048876,"domain_scores_codex":[0.9992571,0.0001765201,0.00004270153,0.0002048667,0.0002220397,0.00009674275],"domain_scores_gemma":[0.9944766,0.002390058,0.000858219,0.0007116623,0.000833426,0.0007300694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001706712,0.0005157518,0.153733,0.001440849,0.0002060621,0.008041963,0.07939132,0.001310057,0.03820806,0.02647926,0.08758532,0.6013817],"study_design_scores_gemma":[0.00005694647,0.001586948,0.1701529,0.000548259,0.000243742,0.01491611,0.06770287,0.005352984,0.03112342,0.02558643,0.6824148,0.000314681],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6932119,0.002581485,0.04460109,0.009835678,0.0008177321,0.0001718988,0.0006885466,0.001416386,0.2466754],"genre_scores_gemma":[0.9323856,0.0009614694,0.008931778,0.002651379,0.0001146421,0.00003484309,0.0002952481,0.0001262504,0.05449885],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02570307,"threshold_uncertainty_score":0.08598536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1021947578849688,"score_gpt":0.4264046197687834,"score_spread":0.3242098618838145,"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."}}