{"id":"W2085415938","doi":"10.1016/j.compcom.2006.09.005","title":"Uncovering hidden maps: Illustrative narratology for digital artists/designers","year":2006,"lang":"en","type":"article","venue":"Computers & composition/Computers and composition","topic":"Digital Storytelling and Education","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University","keywords":"Narratology; Narrative; Storytelling; Reading (process); Computer science; Digital storytelling; Digital media; Multimedia; Narrative structure; Process (computing); Visual arts; Art; Literature; World Wide Web; Linguistics; Philosophy; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0002117624,0.0003966545,0.0004825036,0.0002321139,0.001376661,0.0002659098,0.0002318726,0.0002312209,0.00001199225],"category_scores_gemma":[0.000004983412,0.0004218028,0.0001635009,0.000228836,0.000197223,0.0006840754,0.000118618,0.0003339858,0.00006071317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000331887,"about_ca_system_score_gemma":0.0001182611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009867555,"about_ca_topic_score_gemma":0.000007527674,"domain_scores_codex":[0.9974644,0.000185186,0.0007569136,0.0006749171,0.0002346702,0.0006839176],"domain_scores_gemma":[0.9982134,0.0006894144,0.0003564675,0.0002693304,0.0002640699,0.0002073714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003114319,0.00367914,0.01701878,0.002649597,0.00105753,0.0001550457,0.01969666,0.03536887,0.02903827,0.1846035,0.484166,0.2194522],"study_design_scores_gemma":[0.03931511,0.01001301,0.1126298,0.01217991,0.001197732,0.001427348,0.01291828,0.2928523,0.00846311,0.3243581,0.1711433,0.01350197],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.484737,0.0001898671,0.5073271,0.001228327,0.002550045,0.001013053,0.0001116864,0.0003334165,0.002509523],"genre_scores_gemma":[0.9798717,0.00001032724,0.01587476,0.0009020712,0.00119342,0.0001572668,0.00173188,0.00004858786,0.0002099656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4951347,"threshold_uncertainty_score":0.9999234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02248099967626628,"score_gpt":0.3054956507815765,"score_spread":0.2830146511053102,"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."}}