{"id":"W2751881915","doi":"10.14236/ewic/eva2017.60","title":"Engagement with Artificial Intelligence through Natural Interaction Models","year":2017,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Avatar; Conversation; Human–computer interaction; Creativity; Natural (archaeology); Dialog system; Ambient intelligence; Chatbot; Expression (computer science); Virtual agent; Multimedia; Artificial intelligence; World Wide Web; Psychology; Communication; Dialog box","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":[0.001329688,0.0008603967,0.0003982051,0.0006354095,0.0009992556,0.004572876,0.001380505,0.001761507,0.007478966],"category_scores_gemma":[0.00414335,0.0005253382,0.0009525588,0.0003265955,0.003001121,0.004559588,0.0031471,0.001590394,0.001191598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001260947,"about_ca_system_score_gemma":0.0009512981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002071041,"about_ca_topic_score_gemma":0.001685321,"domain_scores_codex":[0.9979916,0.001180313,0.00005901777,0.0003183589,0.0003466401,0.0001040452],"domain_scores_gemma":[0.998256,0.001168612,0.00011205,0.0002458274,0.0001149005,0.0001024904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001423574,0.0003300229,0.00242623,0.0003254824,0.00007956441,0.0003984379,0.009142737,0.0937757,0.005417763,0.847864,0.002700298,0.03739746],"study_design_scores_gemma":[0.00008236427,0.0001721836,0.0009884584,0.00009646169,0.00003470558,0.0002524462,0.001453056,0.514125,0.001083532,0.4505017,0.03116033,0.00004972436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0722191,0.0007947396,0.7980478,0.003719856,0.0001039329,0.0003568649,0.0001909705,0.0007624954,0.1238043],"genre_scores_gemma":[0.8528653,0.0006380326,0.1215245,0.0003574389,0.00006679497,0.0009463699,0.000210739,0.0001098575,0.02328085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007478966,"threshold_uncertainty_score":0.02501959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06165613229559615,"score_gpt":0.3242827823577143,"score_spread":0.2626266500621182,"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."}}