{"id":"W4244670045","doi":"10.22215/etd/2015-10904","title":"Investigating the Potential of Tabletop Natural User Interfaces Tools in Improving the Nunaliit Cybercartographic Atlas Framework","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Usability; Human–computer interaction; Computer science; User interface; Interface (matter); Gesture; Process (computing); Natural (archaeology); Multimedia; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005926655,0.0003155663,0.0003320804,0.0001947835,0.0001780767,0.0004227444,0.001967736,0.0002299788,0.0000285016],"category_scores_gemma":[0.0005548038,0.0001746316,0.0001914178,0.0007437043,0.0001154213,0.0008908611,0.000266334,0.001275302,0.00001363669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005488603,"about_ca_system_score_gemma":0.0002205099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001568261,"about_ca_topic_score_gemma":0.0008327835,"domain_scores_codex":[0.9978926,0.0002298556,0.0005194477,0.0004561573,0.0005371443,0.0003648043],"domain_scores_gemma":[0.9978769,0.0004731635,0.0005039012,0.0006448268,0.0004542033,0.00004694763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002260536,0.0002648532,0.004487477,0.0005250692,0.0008157414,0.00003955967,0.06417967,0.001238638,0.6844773,0.1961567,0.01380557,0.03378344],"study_design_scores_gemma":[0.001795544,0.0007552054,0.2214684,0.005590206,0.0004687014,0.00008601844,0.1293113,0.06692062,0.4939007,0.07383049,0.002354441,0.003518417],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869487,0.0008487613,0.004657714,0.0005212681,0.002742098,0.0004850435,0.000008133704,0.0000192881,0.003768963],"genre_scores_gemma":[0.9964213,0.00001510565,0.001476023,0.0004932145,0.0001162201,0.00003611196,0.00006205469,0.00001962546,0.001360293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2169809,"threshold_uncertainty_score":0.7121269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583422349811149,"score_gpt":0.2803105001129367,"score_spread":0.2644762766148252,"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."}}