{"id":"W2798796014","doi":"10.1145/3170427.3186509","title":"SpaceHopper","year":2018,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00002728595,0.00003094487,0.00002607386,0.00002333479,0.00004212045,0.00003252074,0.0002330825,0.00001019498,0.0004481541],"category_scores_gemma":[0.000007814488,0.00002339599,0.00001908365,0.00007784962,0.00002182839,0.0002982611,0.00007590119,0.00002221401,0.003578323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006353185,"about_ca_system_score_gemma":0.000008637444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001060652,"about_ca_topic_score_gemma":0.000003299276,"domain_scores_codex":[0.9997149,0.000006849335,0.00002992496,0.0001030532,0.00005061192,0.00009466428],"domain_scores_gemma":[0.9997164,0.000009826798,0.000008346608,0.000169276,0.00007317328,0.00002300164],"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":[0.000003117617,0.00002505576,0.000671678,6.076621e-7,0.000009680147,0.000003849526,0.0006145851,9.291801e-8,0.0836359,0.7504475,0.1613268,0.003261105],"study_design_scores_gemma":[0.0002016029,0.0002607484,0.02251299,0.000005638078,0.000001705363,0.00001865083,0.0001319885,0.005560192,0.6707804,0.003312434,0.297013,0.0002005914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005644045,0.000002872802,0.5533525,0.001175787,0.0002953385,0.00001537682,8.125279e-8,0.00001364133,0.4395004],"genre_scores_gemma":[0.982888,4.674981e-7,0.006173349,0.002980006,0.00009216285,8.559943e-7,1.340662e-7,0.00000141905,0.007863552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.977244,"threshold_uncertainty_score":0.9971975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009473524997101832,"score_gpt":0.2565041456921484,"score_spread":0.2470306206950465,"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."}}