{"id":"W4313384440","doi":"10.1007/978-3-031-05214-9_17","title":"Working with Intelligent Narrative Technologies","year":2022,"lang":"en","type":"book-chapter","venue":"Human-computer interaction series","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Narrative; Computer science; Variety (cybernetics); Emerging technologies; Authoring system; Multimedia; Human–computer interaction; Artificial intelligence","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":[0.0007730386,0.0006809582,0.0002365135,0.0008505564,0.00152705,0.007809484,0.000973829,0.001387647,0.042461],"category_scores_gemma":[0.001985461,0.0003168786,0.0002982378,0.000715541,0.002347801,0.01148707,0.002993216,0.001755309,0.01082584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009398212,"about_ca_system_score_gemma":0.0008602627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006508581,"about_ca_topic_score_gemma":0.001260923,"domain_scores_codex":[0.9994766,0.0001986483,0.0000231571,0.00007491374,0.0001753769,0.00005136809],"domain_scores_gemma":[0.9995649,0.0002147369,0.00002333028,0.0000810713,0.00006074809,0.00005515453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001002664,0.00003035265,0.0001152715,0.0001391457,0.000006575292,0.0001061555,0.004908238,0.000253713,0.0007119313,0.8161781,0.05065227,0.1268881],"study_design_scores_gemma":[0.000002840889,0.000007734225,0.00008471923,0.0001649215,0.000004278567,0.0001814748,0.001858662,0.0004124495,0.0006180386,0.1248157,0.8718432,0.000006018781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.003267877,0.005278704,0.04785203,0.003285848,0.0004876503,0.00003625484,0.00007098799,0.000302376,0.9394182],"genre_scores_gemma":[0.09896962,0.01003841,0.05174988,0.001435574,0.0003024767,0.0001434257,0.0003937188,0.0003852991,0.8365815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.042461,"threshold_uncertainty_score":0.1420462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08346511182751715,"score_gpt":0.3001242777943157,"score_spread":0.2166591659667986,"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."}}