{"id":"W4210748065","doi":"10.1108/9781802623659","title":"Designing XR: A Rhetorical Design Perspective for the Ecology of Human+Computer Systems","year":2022,"lang":"en","type":"book","venue":"","topic":"Information Systems Theories and Implementation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Perspective (graphical); Rhetorical question; Ecology; Computer science; Sociology; Biology; Artificial intelligence; Linguistics; Philosophy","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002698746,0.0001263549,0.0003014099,0.000100014,0.001424637,0.00008910587,0.0003297611,0.0001454319,0.000968466],"category_scores_gemma":[0.00006174655,0.00009423393,0.000142528,0.00008634356,0.0001521968,0.0001370223,0.00006177405,0.0001353014,0.000009370746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234338,"about_ca_system_score_gemma":0.0007469714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001216425,"about_ca_topic_score_gemma":0.0001270639,"domain_scores_codex":[0.9982538,0.0004455028,0.0005075838,0.0001545342,0.0004067087,0.0002319209],"domain_scores_gemma":[0.9971245,0.001719818,0.0005480385,0.00014045,0.0004336331,0.00003359059],"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":[0.00001165441,0.000005151371,0.000002256126,0.00002790793,0.00008103726,1.563976e-7,0.03104489,0.0001868614,0.00000161713,0.8185086,0.1499722,0.0001576244],"study_design_scores_gemma":[0.0003392299,0.000471725,0.000004519806,0.00002104616,0.00008027477,0.000001814251,0.1468225,0.0004599543,0.000006968279,0.01130681,0.8402927,0.0001924852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00000191496,0.0001213869,0.5563898,0.0001961568,0.002675141,0.002900139,0.00003469653,0.00004885499,0.4376319],"genre_scores_gemma":[0.005422679,0.00004578396,0.003320325,0.0002079104,0.003572429,0.001084271,0.00007097257,0.00003842503,0.9862372],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8072018,"threshold_uncertainty_score":0.9999448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0960210290404827,"score_gpt":0.3756548491146249,"score_spread":0.2796338200741422,"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."}}