{"id":"W6990327243","doi":"","title":"3D Artefacts: Enriching User Interaction with Your Collections","year":2008,"lang":"en","type":"article","venue":"NPARC","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); Zoom; Cultural heritage; Space (punctuation); Software; Pipeline (software)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001256996,0.0007722067,0.0003488508,0.001249663,0.001359532,0.004339424,0.000955735,0.001063492,0.01246152],"category_scores_gemma":[0.004217658,0.0003637816,0.0006543688,0.001203484,0.0009939233,0.003267755,0.005779753,0.0006574237,0.0022866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000367934,"about_ca_system_score_gemma":0.0004100017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00205136,"about_ca_topic_score_gemma":0.006895183,"domain_scores_codex":[0.9993802,0.0002729097,0.00002651722,0.00005568608,0.0001964284,0.00006815518],"domain_scores_gemma":[0.9986318,0.000774966,0.00006156998,0.0002833924,0.0001137525,0.0001345276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009516477,0.00024603,0.01034781,0.001928958,0.0001241097,0.003976412,0.1592689,0.002249632,0.05791792,0.03010223,0.08606412,0.6468222],"study_design_scores_gemma":[0.0001078287,0.0003764706,0.01980908,0.000712787,0.0001592196,0.00375213,0.01978871,0.004001572,0.01075987,0.01245736,0.9278433,0.0002317999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3923791,0.005253797,0.3351484,0.003224829,0.0005966797,0.0007423473,0.00208056,0.01640479,0.2441696],"genre_scores_gemma":[0.7016108,0.003615849,0.2326577,0.001030481,0.0002779135,0.0007614957,0.001463756,0.002945451,0.05563655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01246152,"threshold_uncertainty_score":0.04168791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02226272384648959,"score_gpt":0.2529164350667312,"score_spread":0.2306537112202416,"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."}}