{"id":"W6963283770","doi":"10.20380/gi2017.20","title":"Ivy: Exploring Spatially Situated Visual Programming for Authoring and Understanding Intelligent Environments","year":2017,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Situated; Debugging; Visual programming language; Programming by demonstration; Visualization; Situated learning","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":[0.001098158,0.0009558125,0.0003725279,0.0004797312,0.000689331,0.002713717,0.001691892,0.001065039,0.007241257],"category_scores_gemma":[0.003972208,0.0004749541,0.0007727668,0.0002758797,0.00259947,0.003101393,0.004938979,0.001184976,0.000987209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005508473,"about_ca_system_score_gemma":0.0005978298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001127331,"about_ca_topic_score_gemma":0.001912852,"domain_scores_codex":[0.9992688,0.0004056501,0.0000232025,0.0001164502,0.0001024979,0.00008342723],"domain_scores_gemma":[0.9984766,0.00105281,0.00007709912,0.0001781107,0.00007644924,0.0001390175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007885006,0.0004517733,0.004414728,0.002396797,0.0001172131,0.003803005,0.08489238,0.08688596,0.1366734,0.3901774,0.01525636,0.2741424],"study_design_scores_gemma":[0.0003751867,0.0008143723,0.002715966,0.0008493865,0.0001299479,0.003390061,0.01454741,0.253,0.06393611,0.2203892,0.4396024,0.0002498937],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03478345,0.0002524899,0.9457715,0.0004656195,0.00005363657,0.0001256725,0.0001013995,0.00354034,0.01490601],"genre_scores_gemma":[0.3865278,0.0006031878,0.5991114,0.0002283356,0.00003664114,0.0004221109,0.0002444902,0.001252326,0.01157374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007241257,"threshold_uncertainty_score":0.0242244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.179137195517694,"score_gpt":0.3349232310311058,"score_spread":0.1557860355134118,"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."}}