{"id":"W2966384680","doi":"","title":"Conversational Agents as Historical Figures: Individual Differences and Perceptions of Agent and Social Presence","year":2016,"lang":"en","type":"article","venue":"EdMedia + Innovate Learning","topic":"AI in Service Interactions","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Perception; Psychology; History","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":[0.0001967357,0.0001100451,0.0001459053,0.0001503558,0.0002386731,0.0000672362,0.0003174371,0.00007373222,0.0001988667],"category_scores_gemma":[0.000236794,0.00008674803,0.00002385198,0.0002395919,0.0001479061,0.0004788843,0.0003279104,0.0002234954,0.00003228636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008912393,"about_ca_system_score_gemma":0.00006432849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000624017,"about_ca_topic_score_gemma":0.000007719977,"domain_scores_codex":[0.9988036,0.0001022062,0.0002507507,0.0002889138,0.0003705692,0.000184028],"domain_scores_gemma":[0.9990742,0.0004340335,0.0001737824,0.000115365,0.0001464859,0.00005613461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000377367,0.0002104457,0.7268167,0.0001262233,0.0001926443,0.00002670238,0.08215587,0.00001449443,0.01640473,0.06148722,0.01432594,0.09820129],"study_design_scores_gemma":[0.000771526,0.0002372469,0.9678461,0.0001290133,0.00002288401,0.00004005116,0.001553196,0.001652399,0.0002072906,0.00602055,0.02116952,0.0003502189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768663,0.00003409036,0.01219739,0.009854921,0.0005898722,0.00007743365,0.000006025077,0.00006378216,0.0003101917],"genre_scores_gemma":[0.9967546,0.0000417423,0.001867049,0.0001816332,0.0001505921,0.00001329734,0.000003966261,0.000006211857,0.0009808578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2410294,"threshold_uncertainty_score":0.3537482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03267979765278572,"score_gpt":0.278943032939987,"score_spread":0.2462632352872013,"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."}}