{"id":"W2556146372","doi":"10.1145/2992154.2996359","title":"Collaboration Meets Interactive Surfaces and Spaces (CMIS)","year":2016,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer-supported cooperative work; Computer science; Human–computer interaction; Wearable computer; Scale (ratio); Collaborative software; Work (physics); Data science; World Wide Web; Engineering; Geography","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":[0.00006670249,0.00007881061,0.00007623405,0.00005201174,0.00005975864,0.0001588332,0.000171396,0.00002338649,0.00007359272],"category_scores_gemma":[0.0000544604,0.00004624618,0.00001639497,0.0001169922,0.0000329879,0.001953391,0.0001040701,0.00002683974,0.0001225222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002719229,"about_ca_system_score_gemma":0.00002411951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003118857,"about_ca_topic_score_gemma":0.00003720495,"domain_scores_codex":[0.9994404,0.00004024748,0.00007879599,0.0002267423,0.00009396221,0.0001198523],"domain_scores_gemma":[0.9994262,0.0001664272,0.00005078755,0.0001413895,0.0001724792,0.00004272902],"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":[0.00004879328,0.00005525345,0.003954368,0.000005405149,0.00005943832,0.000009623911,0.002960485,0.000002744738,0.7845553,0.1863816,0.0124733,0.009493693],"study_design_scores_gemma":[0.0007946253,0.0003152978,0.03393768,0.00007884071,0.000008262264,0.00001832262,0.001826718,0.003222538,0.9215545,0.002713547,0.03515947,0.0003701733],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6241418,0.0001263863,0.3040694,0.02904172,0.0008696361,0.0002069657,0.000008254646,0.00005547973,0.0414803],"genre_scores_gemma":[0.9953559,0.00003769596,0.00241259,0.0003425473,0.00002157846,0.000004072504,4.179082e-7,0.000002969541,0.001822197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3712141,"threshold_uncertainty_score":0.1885865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007432316926376008,"score_gpt":0.2551294283064962,"score_spread":0.2476971113801202,"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."}}