{"id":"W2098930842","doi":"10.1109/tabletop.2007.18","title":"Going Deeper: a Taxonomy of 3D on the Tabletop","year":2007,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Taxonomy (biology); Computer science; Realm; Data science; Human–computer interaction; Dimension (graph theory); Management science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002555886,0.00005518951,0.00005999487,0.00004395351,0.00005611124,0.00002214989,0.0003972636,0.0000160152,0.0001368308],"category_scores_gemma":[0.00003479469,0.00003291572,0.00003870044,0.0001431641,0.00002160375,0.0001808222,0.00008143343,0.00007130053,0.0001740326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001777468,"about_ca_system_score_gemma":0.00001632966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002760312,"about_ca_topic_score_gemma":0.00000691656,"domain_scores_codex":[0.9995022,0.00001635618,0.0001031895,0.0001204838,0.0001036058,0.0001541843],"domain_scores_gemma":[0.9993485,0.0002608993,0.00004623795,0.0002578509,0.0000655111,0.00002095054],"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":[0.00001640394,0.00006573157,0.001193924,0.000003532053,0.00002352764,0.000005112311,0.0004123024,0.00001291601,0.03245738,0.951512,0.006701221,0.007595976],"study_design_scores_gemma":[0.0002538885,0.0002386736,0.009482988,0.00003993799,0.000005165062,0.00001032354,0.0005800545,0.004257676,0.8647028,0.0007672269,0.1194653,0.0001960003],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03787138,0.00001020197,0.6822603,0.0003682938,0.0001290179,0.00008909231,2.879068e-7,0.000006143898,0.2792653],"genre_scores_gemma":[0.9889988,0.000001178201,0.007402005,0.002366651,0.00002670872,0.000004707973,2.099198e-7,0.000002250042,0.001197539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9511274,"threshold_uncertainty_score":0.2236894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02686035894641325,"score_gpt":0.2467018591260424,"score_spread":0.2198415001796292,"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."}}